Affectivity in the #jesuisCharlie Twitter discussion

Marjut Johansson and Veronika Laippala

Abstract

The Twitter discussion with the hashtag #jesuisCharlie was a large-scale social media event commenting on the tragic terrorist attack that took place in Paris in 2015. In this paper, we analyze French tweets compiled with language technology methods from a large dataset. Our qualitative approach determines what types of affectivity are expressed. According to our results, first, core emotions are shared, and they are based on the identification with the internet meme je suis Charlie (I am Charlie). In them, participants show their commitment to democratic values and freedom of speech, as well as grief. They build up a we-agency and togetherness between the networked participants. Second, participants disalign from those who do not share the same values or who are a threat to them. Here, the emotions range from irritation and doubt to anger and disgrace, manifesting awayness. They contain protest against how democratic values are violated.

Keywords:
Publication history
Table of contents

1.Introduction

In the terrorist attack on the editorial office of Charlie Hebdo in Paris and the subsequent follow-up attacks, 17 people were killed by three terrorists in January 2015. The terrorists were shot by the police at the end of a three-day pursuit (Johansson et al. 2018Johansson, Marjut, Aki-Juhani Kyröläinen, Filip Ginter, Lotta Lehti, Attila Krizsán, and Veronika Laippala 2018 ”Opening Up #jesuisCharlie Anatomy of a Twitter Discussion With Mixed Methods.” Journal of Pragmatics 129: 90–101. CrossrefGoogle Scholar, 90). Later, it was discovered that this act of violence was domestic, as the terrorists were French citizens (Nugier and Guimond 2016Nugier, Armelle, and Serge Guimond 2016« Je suis Charlie » New Findings on the Social and Political Psychology of Terrorism. International Review of Social Psychology 29 (1): 45–49. CrossrefGoogle Scholar, 45). Charlie Hebdo is a French satirical left-wing magazine that has been controversial since its inception in the 1960s, but its journalism has been appreciated because of its critical attitude.

This disruptive news event attracted huge local and global public attention, both offline and online. It gathered people for marches, not only in Paris, but also in several places across the world in expression of solidarity and freedom of speech. In addition, various social media platforms became places of sharing information and expressing emotions, and they were used cross-media by networking public in this polymedia event (cf. Madianou and Miller 2013Madianou, Mirca, and Daniel Miller 2013 “Polymedia: Towards a New Theory of Digital Media in Interpersonal Communication.” International Journal of Cultural Studies 16 (2): 169–187. CrossrefGoogle Scholar). Quickly, the slogan je suis Charlie (I am Charlie) became an internet meme (De Cock and Pizarro Pedraza 2018De Cock, Barbara, and Andrea Pizarro Pedraza 2018 “From Expressing Solidarity to Mocking on Twitter: Pragmatic Functions of Hashtags Starting With #jesuis Across Languages.” Language in Society 47 (2), 197–217. CrossrefGoogle Scholar, 1). On Twitter, tweeting with the hashtag #jesuisCharlie and other related hashtags represented one of the most tweeted news events of its time (Giaxoglou 2018Giaxoglou, Korina 2018 “JeSuisCharlie? Hashtags as Narrative Resources in Contexts of Ecstatic Sharing.” Discourse, Context & Media 22: 13–20. CrossrefGoogle Scholar; Johansson et al. 2018Johansson, Marjut, Aki-Juhani Kyröläinen, Filip Ginter, Lotta Lehti, Attila Krizsán, and Veronika Laippala 2018 ”Opening Up #jesuisCharlie Anatomy of a Twitter Discussion With Mixed Methods.” Journal of Pragmatics 129: 90–101. CrossrefGoogle Scholar). In sum, this event fulfills characteristics that are typical of the global age: it concentrated on a specific thematic core; it was a translocal, situated cross-media event; and it had shared experiences that reached wide and diverse audiences and participants (Hepp and Couldry 2010Hepp, Andreas, and Nick Couldry 2010 “Introduction: Media Events in Globalized Media Cultures.” In Media Events in a Global Age, ed. by Andreas Hepp, Nick Couldry, and Friedrich Krotz, 1–20. Abingdon: Routledge.Google Scholar).

In this paper, our main objective is to study the public display of affectivity related to this Twitter discussion in French. Social media offer individuals and large audiences public spaces for expression, but these spaces involve individual and subjective reactivity (cf. Johansson 2017Johansson, Marjut 2017Everyday Opinions in News Discussion Forums: Public Vernacular Discourse. Discourse, Context and Media (19), 5–12. CrossrefGoogle Scholar). In this specific situation, tweets were posted as reactions to the unfolding events and all their implications in the following days. We dissect what types of emotions were expressed, including their forms and intensity. We are interested in the evaluative content they reflect, by which we refer to the kinds of norms and values they build on (cf. Salmela and Nagatsu 2017Salmela, Mikko, and Nagatsu, Michiru 2017 “How Does It Really Feel to Act Together? Shared Emotions and The Phenomenology of We-Agency”. Phenomenology and the Cognitive Sciences 16, 449–470. CrossrefGoogle Scholar; for evaluative content see Section 3). Our research questions are as follows:

  1. How are emotions expressed and shared in the French tweets? What is their function?

  2. How do participants position themselves in affective tweets? Do they align or disalign themselves with shared emotions?

As our premise, based on previous studies on the #jesuisCharlie discussion on social media (De Cock and Pizarro Pedraza 2017; Giaxoglou 2018Giaxoglou, Korina 2018 “JeSuisCharlie? Hashtags as Narrative Resources in Contexts of Ecstatic Sharing.” Discourse, Context & Media 22: 13–20. CrossrefGoogle Scholar; Johansson et al. 2018Johansson, Marjut, Aki-Juhani Kyröläinen, Filip Ginter, Lotta Lehti, Attila Krizsán, and Veronika Laippala 2018 ”Opening Up #jesuisCharlie Anatomy of a Twitter Discussion With Mixed Methods.” Journal of Pragmatics 129: 90–101. CrossrefGoogle Scholar), we can say that shared emotions include expressions of solidarity and grief, which constitute the core of these emotions. Furthermore, we formulate a hypothesis that there will be other types of affectivity, as the media event was complex and engaged the public in different ways (cf. Johansson et al. 2018Johansson, Marjut, Aki-Juhani Kyröläinen, Filip Ginter, Lotta Lehti, Attila Krizsán, and Veronika Laippala 2018 ”Opening Up #jesuisCharlie Anatomy of a Twitter Discussion With Mixed Methods.” Journal of Pragmatics 129: 90–101. CrossrefGoogle Scholar). The affectivity includes emotions that evaluate the core of the togetherness, question it, and even try to delegitimize it (Johansson et al. 2018Johansson, Marjut, Aki-Juhani Kyröläinen, Filip Ginter, Lotta Lehti, Attila Krizsán, and Veronika Laippala 2018 ”Opening Up #jesuisCharlie Anatomy of a Twitter Discussion With Mixed Methods.” Journal of Pragmatics 129: 90–101. CrossrefGoogle Scholar). Our study differs from the previous ones in that it starts with the view that, in a large-scale Twitter discussion, not all the emotions expressed are shared by all the participants (see Section 2). In addition, in contrast to other studies on this Twitter discussion, here we focus only on tweets written in French.

Theoretically, our study is situated at the intersection of sociological and linguistic approaches. First, concerning affectivity and emotions, we apply an affective phenomenology of joint action (Salmela and Nagatsu 2017Salmela, Mikko, and Nagatsu, Michiru 2017 “How Does It Really Feel to Act Together? Shared Emotions and The Phenomenology of We-Agency”. Phenomenology and the Cognitive Sciences 16, 449–470. CrossrefGoogle Scholar), as well as an approach to stance and positioning (Du Bois 2007Du Bois, John 2007 “The Stance Triangle.” In Stancetaking in Discourse. Subjectivity, Evaluation and Interaction, ed. by Robert Englbretson, 139–182. Amsterdam/Philadelphia: John Benjamins Publishing Company. CrossrefGoogle Scholar). Second, our theoretical and methodological approaches are complementary. The corpus linguistic methods give us the possibility of gaining insight into a large dataset, while the digital discourse analysis is the perspective on how interactants create meaning and express their views in the digital context (Zappavigna 2017Zappavigna, Michele 2017 “Twitter.” In Pragmatics of Social Media, ed. by Christian Hoffmann, and Wolfram Bublitz, 201–224. Berlin/Boston: De Gruyter Mouton. CrossrefGoogle Scholar). The framework on affect first builds on linguistic approaches (Ochs and Schiefflin 1989Ochs, Elinor, and Bambi Schiefflin 1989 ”Language Has a Heart.” Text 9 (1): 7–25. CrossrefGoogle Scholar; Biber and Finegan 1989Biber, Douglas and Edward Finegan 1989 “Styles of Stance in English: Lexical and Grammatical Marking of Evidentiality and Affect.” Text 9 (1), 93–121. CrossrefGoogle Scholar), followed by the phenomenology of joint action (Salmela and Nagatsu 2017Salmela, Mikko, and Nagatsu, Michiru 2017 “How Does It Really Feel to Act Together? Shared Emotions and The Phenomenology of We-Agency”. Phenomenology and the Cognitive Sciences 16, 449–470. CrossrefGoogle Scholar), and, finally, media and culture studies on affect (Ahmed 2015Ahmed, Sara 2015The Cultural Politics of Emotion. Routledge, New York & London.Google Scholar; Papacharissi 2015Papacharissi, Zizi 2015Affective Publics. Sentiment, Technology, and Politics. Oxford: Oxford University Press.Google Scholar).

In Section 2, we discuss research on #jesuisCharlie; then, in Section 3, we consider affectivity. We present our data in Section 4 and our analysis in Sections 57. In Section 8, we conclude the paper.

2.Research on #jesuisCharlie and large-scale Twitter discussions

Several studies have analyzed the Charlie Hebdo terrorist attack from the perspective of media events and public reactions on social media. Research in linguistics has examined various themes. Bouko et al. (2017)Bouko, Catherine, Laura Calabrese, and Orphée De Clercq 2017 “Cartoons as Interdiscourse: A Quali-quantitative Analysis of Social Representations Based on Collective Imagination in Cartoons Produced After the Charlie Hebdo Attack.” Discourse, Context & Media 15: 24–33. CrossrefGoogle Scholar identified various thematic categories of cartoons, such as the pen fighting the sword, freedom of speech, and the journalist as a hero. The use of the hashtag #jesuisCharlie has been studied along with other frequent hashtags, such as #CharlieHebdo. De Cock and Pizarro Pedraza (2018)De Cock, Barbara, and Andrea Pizarro Pedraza 2018 “From Expressing Solidarity to Mocking on Twitter: Pragmatic Functions of Hashtags Starting With #jesuis Across Languages.” Language in Society 47 (2), 197–217. CrossrefGoogle Scholar analyzed the different hashtags, starting with je suis: (I am) #jesuisAhmed (I am Ahmed) and #jesuisKouachi (I am Kouachi). The former refers to one of the police officers killed in the attack, while the latter names the two terrorist brothers. These researchers point out that this type of identification goes back to famous political moments expressing solidarity, namely Ich bin ein Berliner (De Cock and Pizarro Pedraza 2018De Cock, Barbara, and Andrea Pizarro Pedraza 2018 “From Expressing Solidarity to Mocking on Twitter: Pragmatic Functions of Hashtags Starting With #jesuis Across Languages.” Language in Society 47 (2), 197–217. CrossrefGoogle Scholar, 6). In the case of #jesuisCharlie, the identification je suis expressed mainly solidarity and condolences:

The initial hashtag #jesuisCharlie establishes a direct identification between the speaker and Charlie Hebdo. The use of je suis ‘I am’ creates an identification between the speaker and Charlie, which, in turn, is a metonym for the staff of the magazine and/or for what happened to them.(De Cock and Pizarro Pedraza 2018De Cock, Barbara, and Andrea Pizarro Pedraza 2018 “From Expressing Solidarity to Mocking on Twitter: Pragmatic Functions of Hashtags Starting With #jesuis Across Languages.” Language in Society 47 (2), 197–217. CrossrefGoogle Scholar, 6)

Giaxoglou (2018)Giaxoglou, Korina 2018 “JeSuisCharlie? Hashtags as Narrative Resources in Contexts of Ecstatic Sharing.” Discourse, Context & Media 22: 13–20. CrossrefGoogle Scholar analyzed the phases, emergence, and circulation of the hashtags #jesuisCharlie and #CharlieHebdo during this event. She considered these hashtags as metalinguistic and metadiscursive markers and found that they were used for narrative purposes (Giaxoglou 2018Giaxoglou, Korina 2018 “JeSuisCharlie? Hashtags as Narrative Resources in Contexts of Ecstatic Sharing.” Discourse, Context & Media 22: 13–20. CrossrefGoogle Scholar, 15–16). According to this researcher, they allowed for the emergence of an “affective public, banding and bonding around shows of solidarity” (Giaxoglou 2018Giaxoglou, Korina 2018 “JeSuisCharlie? Hashtags as Narrative Resources in Contexts of Ecstatic Sharing.” Discourse, Context & Media 22: 13–20. CrossrefGoogle Scholar, 16).

Another set of studies analyzed large-scale data or used mixed methods in their approach. In this research, English and French tweets have been categorized using cluster analysis (Smyrnaois and Ratinaud 2017) and a text-mining approach (Giglietto and Lee 2015Giglietto, Fabio, and Yenn Lee 2015 “To Be or Not to Be Charlie: Twitter Hashtags as a Discourse and Counter-discourse in the Aftermath of the 2015 Charlie Hebdo Shooting in France.” In Proceedings of the 5th Workshop on Making Sense of Microposts, ed. by Matthew Rowe, Milan Stankovic, and Aba-Sah Dadzie, 33–37. Florence: CEUR Workshop Proceedings (CEUR-WS.org). http://​ceur​-ws​.org/.). Smyrnaios and Ratinaud (2017)Smyrnaios, Nikos, and Pierre Ratinaud 2017 “The Charlie Hebdo Attacks on Twitter: A Comparative Analysis of a Political Controversy in English and French.” Social Media + Society 3 (1): 1–13. CrossrefGoogle Scholar determined themes in tweeting, ranging from freedom of speech, journalism, and condolences to expressions of horror and fanaticism, to name a few. Giglietto and Lee (2015Giglietto, Fabio, and Yenn Lee 2015 “To Be or Not to Be Charlie: Twitter Hashtags as a Discourse and Counter-discourse in the Aftermath of the 2015 Charlie Hebdo Shooting in France.” In Proceedings of the 5th Workshop on Making Sense of Microposts, ed. by Matthew Rowe, Milan Stankovic, and Aba-Sah Dadzie, 33–37. Florence: CEUR Workshop Proceedings (CEUR-WS.org). http://​ceur​-ws​.org/., 34–35) showed the frequency of posting of tweets and identified the most retweeted posts during the #jesuisCharlie discussion. However, they only mentioned some emotions, such as grief and resistance, in passing (Giglietto and Lee 2015Giglietto, Fabio, and Yenn Lee 2015 “To Be or Not to Be Charlie: Twitter Hashtags as a Discourse and Counter-discourse in the Aftermath of the 2015 Charlie Hebdo Shooting in France.” In Proceedings of the 5th Workshop on Making Sense of Microposts, ed. by Matthew Rowe, Milan Stankovic, and Aba-Sah Dadzie, 33–37. Florence: CEUR Workshop Proceedings (CEUR-WS.org). http://​ceur​-ws​.org/., 27–36). In an analysis of multiple topics and positioning in Twitter discussion in English, Johansson et al. (2018)Johansson, Marjut, Aki-Juhani Kyröläinen, Filip Ginter, Lotta Lehti, Attila Krizsán, and Veronika Laippala 2018 ”Opening Up #jesuisCharlie Anatomy of a Twitter Discussion With Mixed Methods.” Journal of Pragmatics 129: 90–101. CrossrefGoogle Scholar showed how, in this huge Twitter discussion, there is a diversification of positioning, as well as a polarization of stances, from expressions of solidarity or condolences to irony and bashing. These uses have not been examined in detail in the qualitative, small-scale data used in previous research (Giaxoglou 2017; De Cock and Pizarro Pedraza 2018De Cock, Barbara, and Andrea Pizarro Pedraza 2018 “From Expressing Solidarity to Mocking on Twitter: Pragmatic Functions of Hashtags Starting With #jesuis Across Languages.” Language in Society 47 (2), 197–217. CrossrefGoogle Scholar). This is the gap this study sets out to fill, as it will focus on the tweets that were written in French, which originated for the most part from the socio-cultural context in which the terrorist attack took place.

While tweets are short, their multifunctionality allows them to be used for various objectives. From the textual perspective, hashtags may indicate a topic, and they are instances of searchable talk (Zappavigna 2011 2011 “Ambient Affiliation: A Linguistic Perspective on Twitter.” New Media & Society 13 (5): 788–806. CrossrefGoogle Scholar). From a discursive perspective, hashtags are devices by which meaning is created: they can be used for constructing an identity, establishing an interpersonal relationship, or showing alignment or disalignment (Zappavigna 2017Zappavigna, Michele 2017 “Twitter.” In Pragmatics of Social Media, ed. by Christian Hoffmann, and Wolfram Bublitz, 201–224. Berlin/Boston: De Gruyter Mouton. CrossrefGoogle Scholar, 212). They may create what Zappavigna (2014) 2014 “Enacting Identity in Microblogging Through Ambient Affiliation.” Discourse & Communication 2: 209–228. CrossrefGoogle Scholar called ambient affiliation in like-minded groups. According to Giaxoglou (2018Giaxoglou, Korina 2018 “JeSuisCharlie? Hashtags as Narrative Resources in Contexts of Ecstatic Sharing.” Discourse, Context & Media 22: 13–20. CrossrefGoogle Scholar, 14), using hashtags in microblogging is “a practice enacted through linguistic and discourse metafunctions that have implications for modes of sharing and types of audience engagement.”

Twitter discussions differ depending on what types of comments participants are exchanging with others. These can range, for example, from identity building (Page 2012Page, Ruth 2012 “The Linguistics of Self-branding and Micro-celebrity in Twitter: The Role of Hashtags.” Discourse & Communication 6 (2): 181–201. CrossrefGoogle Scholar) to group affiliation (Zappavigna 2011 2011 “Ambient Affiliation: A Linguistic Perspective on Twitter.” New Media & Society 13 (5): 788–806. CrossrefGoogle Scholar). Zappavigna (2017Zappavigna, Michele 2017 “Twitter.” In Pragmatics of Social Media, ed. by Christian Hoffmann, and Wolfram Bublitz, 201–224. Berlin/Boston: De Gruyter Mouton. CrossrefGoogle Scholar, 203, 213) enumerated a wide range of topics. These discussions are not similar, and thus their communicative activities differ as well, ranging, for example, from apologies (Page 2014 2014 “Saying ‘Sorry’: Corporate Apologies Posted on Twitter.” Journal of Pragmatics 62: 30–45. CrossrefGoogle Scholar) to self-praise (Dayter 2016Dayter, Daria 2016Discursive Self in Microblogging: Speech Acts, Stories and Self-praise. Amsterdam/Philadelphia: John Benjamins Publishing Company. CrossrefGoogle Scholar). Large-scale Twitter discussions have taken place, for instance, in the so-called Arab revolution in Egypt or in crisis situations when tweets and other social media platforms have been used for information sharing, as well as for emotional and ideological reasons (Papacharissi 2015Papacharissi, Zizi 2015Affective Publics. Sentiment, Technology, and Politics. Oxford: Oxford University Press.Google Scholar). Therefore, it is interesting to study what types of communication tweets are used for and whether they support the events they are commenting on (Papacharissi 2015Papacharissi, Zizi 2015Affective Publics. Sentiment, Technology, and Politics. Oxford: Oxford University Press.Google Scholar, 7–8). In the case of the networking public, Papacharissi (2015Papacharissi, Zizi 2015Affective Publics. Sentiment, Technology, and Politics. Oxford: Oxford University Press.Google Scholar, 89) discovered that, on the one hand, tweeting gives participants a feeling of being there – being a part of a situation (Papacharissi 2015Papacharissi, Zizi 2015Affective Publics. Sentiment, Technology, and Politics. Oxford: Oxford University Press.Google Scholar, 32). On the other, besides tweeting for the purpose of information, opinion sharing, and expressions of solidarity, there exists a type of tweeting that tends to delegitimize the participants’ sharing of ideas by, for instance, trolling (Papacharissi 2015Papacharissi, Zizi 2015Affective Publics. Sentiment, Technology, and Politics. Oxford: Oxford University Press.Google Scholar, 89). This was found to have taken place in the #jesuisCharlie discussion (Johansson et al. 2018Johansson, Marjut, Aki-Juhani Kyröläinen, Filip Ginter, Lotta Lehti, Attila Krizsán, and Veronika Laippala 2018 ”Opening Up #jesuisCharlie Anatomy of a Twitter Discussion With Mixed Methods.” Journal of Pragmatics 129: 90–101. CrossrefGoogle Scholar).

3.Affect in context

3.1Affect and emotions

What is affect? How does it differ from emotions or feelings? In linguistic approaches, emotion is first considered an embodied, personal, cognitive, and psychological experience that is communicated either linguistically or through bodily expressions (Enfield and Wierzbicka 2002Enfield, Nick J., and Anna Wierzbicka 2002 “The Body in Description of Emotion.” Pragmatics and Cognition 10:½: 1–25. CrossrefGoogle Scholar, 4–6). Researchers have defined emotions from several perspectives, such as the cognitive and social viewpoints, and they either accentuate individual experience or social experience of emotions (see, e.g., Bednarek 2008Bednarek, Monika 2008Emotion Talk Across Corpora. Basingstoke England, New York: Palgrave Macmillan. CrossrefGoogle Scholar, 4–12 for an overview). According to Edwards (1999Edwards, Derek 1999 “Emotion Discourse.” Culture & Psychology 5 (3): 271–291. CrossrefGoogle Scholar, 282), emotions and affectivity are cognitively grounded or cognitively consequential in relation to objects or events.

Here, our starting point is communicative activities and how affectivity is expressed in them. To differentiate between affect and emotion, we turn to the phenomenology of joint action. According to Salmela and Nagatsu (2017Salmela, Mikko, and Nagatsu, Michiru 2017 “How Does It Really Feel to Act Together? Shared Emotions and The Phenomenology of We-Agency”. Phenomenology and the Cognitive Sciences 16, 449–470. CrossrefGoogle Scholar, 451), affect is a phenomenal state that has two types of realizations:

Emotions are felt evaluative responses to specific objects and events and they motivate the subject to act in accordance with evaluative content of the emotion; to fight or flee in danger, to retaliate or retribute when offended, to hide in shame, and so on. Feelings can be part of emotion, and they can be experienced as bodily sensations or intentional feelings directed at the particular object of emotion or as both kinds of feelings at the same time. However, not all feelings such as rapport or alienation are part of emotions.(Salmela and Nagatsu 2017Salmela, Mikko, and Nagatsu, Michiru 2017 “How Does It Really Feel to Act Together? Shared Emotions and The Phenomenology of We-Agency”. Phenomenology and the Cognitive Sciences 16, 449–470. CrossrefGoogle Scholar, 451; our underlining)

Communicative situations are social and cultural situations of joint activity (Linell 2009Linell, Per 2009Rethinking Language, Mind and World Dialogically. Interactional and Contextual Theories of Human Sense-making. Charlotte, NC: Information Age Publishing.Google Scholar, 202). In other words, social actors express affect or emotions that are indexically grounded in situations (see Edwards 1999Edwards, Derek 1999 “Emotion Discourse.” Culture & Psychology 5 (3): 271–291. CrossrefGoogle Scholar). Ochs (1996Ochs, Elinor 1996 “Linguistic Resources for Socializing Humanity.” In Rethinking Linguistic Relativity, ed. by John J. Gumperz, and Stephen C. Levinson, 407–437. Cambridge: Cambridge University Press.Google Scholar, 420) explained this in detail:

In all communities, affective stances are socio-culturally linked to social acts, in the minds of speakers (illocutionary acts), of hearers (perlocutionary acts), or of both speakers and hearers. [… P]articular affects help to constitute the meaning of particular acts. Where these affects are indexed by a linguistic form, that form may also constitutively index associated social acts.(Ochs 1996Ochs, Elinor 1996 “Linguistic Resources for Socializing Humanity.” In Rethinking Linguistic Relativity, ed. by John J. Gumperz, and Stephen C. Levinson, 407–437. Cambridge: Cambridge University Press.Google Scholar, 420)

Here, we consider affectivity and emotions as social acts that are indexical and situated in contexts. Moreover, in social situations, emotions are tied to interpersonal relationships and communicative activities (Linell 2009Linell, Per 2009Rethinking Language, Mind and World Dialogically. Interactional and Contextual Theories of Human Sense-making. Charlotte, NC: Information Age Publishing.Google Scholar, 201–203). In her approach to emotions as social and cultural practices, Ahmed (2015Ahmed, Sara 2015The Cultural Politics of Emotion. Routledge, New York & London.Google Scholar, 10) does not consider emotions as individual expressions from “inside out.” Instead, she proposes a model she calls the sociality of emotions, in which “emotions create the very effect of the surfaces and boundaries that allow all kinds of objects to be delineated. The objects of emotion take shape as effects of circulation” (Ahmed 2015Ahmed, Sara 2015The Cultural Politics of Emotion. Routledge, New York & London.Google Scholar, 10).

In joint communicative activities, emotions are relational: they may be expressed together, or one emotion may have an effect on the co-actors. Emotions create bonds between social actors; they are shared in a way that bond people together (“towardness”), or they separate social actors from each other (“awayness”; Ahmed 2015Ahmed, Sara 2015The Cultural Politics of Emotion. Routledge, New York & London.Google Scholar, 8–9). In addition, emotions, especially negative ones, can function in such a way that differentiation or othering between social actors takes place (Ahmed 2015Ahmed, Sara 2015The Cultural Politics of Emotion. Routledge, New York & London.Google Scholar, 1).

In their phenomenological account of joint action, Salmela and Nagatsu (2017)Salmela, Mikko, and Nagatsu, Michiru 2017 “How Does It Really Feel to Act Together? Shared Emotions and The Phenomenology of We-Agency”. Phenomenology and the Cognitive Sciences 16, 449–470. CrossrefGoogle Scholar considered small-scale, face-to-face situations, such as singing, dancing, and spectating team sports. According to the researchers, shared emotions give a sense of we-agency during and in consequence of joint actions (Salmela and Nagatsu 2017Salmela, Mikko, and Nagatsu, Michiru 2017 “How Does It Really Feel to Act Together? Shared Emotions and The Phenomenology of We-Agency”. Phenomenology and the Cognitive Sciences 16, 449–470. CrossrefGoogle Scholar, 451). When participants have an experience in which they share a similar type of emotion, they have similar evaluative contents and affective experiences, and they are aware of this: “Phenomenologically, the evaluative content and affective experience of an emotion are typically intertwined and intentionally directed at the particular object of emotion. While the evaluative content of an emotion is necessarily intentional, the affective experience is only contingently so” (Salmela and Nagatsu 2017Salmela, Mikko, and Nagatsu, Michiru 2017 “How Does It Really Feel to Act Together? Shared Emotions and The Phenomenology of We-Agency”. Phenomenology and the Cognitive Sciences 16, 449–470. CrossrefGoogle Scholar, 457). In addition, the evaluative content of an emotion contains concerns, such as norms or values, for example (Salmela and Nagatsu 2017Salmela, Mikko, and Nagatsu, Michiru 2017 “How Does It Really Feel to Act Together? Shared Emotions and The Phenomenology of We-Agency”. Phenomenology and the Cognitive Sciences 16, 449–470. CrossrefGoogle Scholar, 457). Emotions also differ in intensity from the weakest type to moderate and the strongest shared emotions, in which the degree of collectivity and concerns are either private or collectively shared (Salmela and Nagatsu 2017Salmela, Mikko, and Nagatsu, Michiru 2017 “How Does It Really Feel to Act Together? Shared Emotions and The Phenomenology of We-Agency”. Phenomenology and the Cognitive Sciences 16, 449–470. CrossrefGoogle Scholar).

3.2Affective stance and positioning

According to Ochs (1996Ochs, Elinor 1996 “Linguistic Resources for Socializing Humanity.” In Rethinking Linguistic Relativity, ed. by John J. Gumperz, and Stephen C. Levinson, 407–437. Cambridge: Cambridge University Press.Google Scholar, 421), in verbally expressed emotions, linguistic elements help in identifying acts that take place with expression of those emotions. Emotions can be expressed explicitly by lexical elements, such as sad or furious, but they can also be communicated in implicit ways (Edwards 1999Edwards, Derek 1999 “Emotion Discourse.” Culture & Psychology 5 (3): 271–291. CrossrefGoogle Scholar, 279). Affect and emotions have been studied in a great range of linguistic studies since the seminal work of Biber and Finegan (1989)Biber, Douglas and Edward Finegan 1989 “Styles of Stance in English: Lexical and Grammatical Marking of Evidentiality and Affect.” Text 9 (1), 93–121. CrossrefGoogle Scholar, which focused on overt lexical and grammatical markers of a speaker’s stance, such as adjectives, adverbials, hedges, and verbs. In her corpus linguistic approach, Bednarek distinguished between emotional talk (signaling function) and emotion talk (denoting function; Bednarek 2008Bednarek, Monika 2008Emotion Talk Across Corpora. Basingstoke England, New York: Palgrave Macmillan. CrossrefGoogle Scholar, 11). She gave the examples of first person use – Oh fuck (signal), I’m really angry (denote) – and other uses – And then he goes “Oh fuck” (signal) and And he was very angry (denote; Bednarek 2008Bednarek, Monika 2008Emotion Talk Across Corpora. Basingstoke England, New York: Palgrave Macmillan. CrossrefGoogle Scholar, 11–12).

To make another distinction, when expressing emotions, social actors may orient toward an object in the world and express their emotion regarding it (something is terrible, nice, bad). Alternatively, they may formulate their own subjective view on it: I hate it (Edwards and Potter 2017Edwards, Derek, and Jonathan Potter 2017 “Some Uses of Subject-side Assessments.” Discourse Studies 19 (5): 497–514. CrossrefGoogle Scholar, 497–498). Edwards and Potter (2017)Edwards, Derek, and Jonathan Potter 2017 “Some Uses of Subject-side Assessments.” Discourse Studies 19 (5): 497–514. CrossrefGoogle Scholar called these O-side (object) or S-side (subject) assessments. O-side assessments are intersubjective and shared, whereas S-side assessments “formulate the evaluation […] restricted to the judgement of the speaker” (Edwards and Potter 2017Edwards, Derek, and Jonathan Potter 2017 “Some Uses of Subject-side Assessments.” Discourse Studies 19 (5): 497–514. CrossrefGoogle Scholar, 511–512), building up the speaker’s position. When using S-side assessments, speakers may manage communicative situations to avoid misunderstandings and disagreement while managing diverse views (Edwards and Potter 2017Edwards, Derek, and Jonathan Potter 2017 “Some Uses of Subject-side Assessments.” Discourse Studies 19 (5): 497–514. CrossrefGoogle Scholar, 511–512). Either way, social actors express a stance with an orientation toward an object. We build on this distinction below (see Section 4).

Twitter discussion can be considered as written interaction in a digital context, situated and temporarily limited in its discussion on a topic. Although we use the term discussion here, the specific characteristics of this social media interaction should be considered, and it should not be compared to face-to-face interactions as such. Participants post tweets as their contributions to this large-scale interaction that can be interactive in the sense that they respond to topic, but they have a choice between directing their post explicitly to other participants with @ or publishing their post without any addressee. However, our data derives from large scale data, and it is not possible to account for this. We will describe it and its limitations in the following section.

4.Data and methods

4.1Large scale data and clustering of tweets

In our data, the #jesuisCharlie hashtag was used in 1.2 million tweets in 51 languages between 7.1.2015 (18:33 h) and 14.1.2015 (06:50 h). They were collected11.Collected by Marco T. Bastos and Raquel Recuero. with the yourTwapperKeeper application (Bruns and Liang 2012Bruns, Axel, and Yuxian Eugene Liang 2012 “Tools and Methods for Capturing Twitter Data During Natural Disasters.” First Monday 17 (4). http://​firstmonday​.org​/ojs​/index​.php​/fm​/article​/view​/3937​/3193. Accessed May 15, 2016. Crossref). In this study, we concentrate on tweets written in French and apply a mixed-methods approach. This allows for the combination of a large-scale quantitative analysis revealing general tendencies found in the entire dataset to a detailed examination of linguistic instances in their usage contexts. The study design consists of two phases, as described below.

In the first phase, our method is applying the large-scale approach of clustering, an exploratory machine learning method used to find structure and groupings in previously unseen data (Kaufman and Rousseeuw 1990Kaufman, Leonard, and Peter J. Rousseeuw 1990Finding Groups in Data: An Introduction to Cluster Analysis. New York: John Wiley. CrossrefGoogle Scholar; Divjak and Fieller 2014Divjak, Dagmar, and Nick Fieller 2014 “Clustering Linguistic Data.” In Corpus Methods for Semantics: Quantitative Studies in Polysemy and Synonymy, ed. by Dylan Glynn, and Justyna Robinson, 405–441. Amsterdam/Philadelphia: John Benjamins Publishing Company. CrossrefGoogle Scholar; Moisl 2015Moisl, Hermann 2015Cluster Analysis for Corpus Linguistics. Berlin: De Gruyter Mouton. CrossrefGoogle Scholar). We use clustering to find thematic groupings in the tweets and group tweets with similar topics together into clusters. This is ensured by constructing a vector space representation for each tweet using word2vec (Mikolov et al. 2013Mikolov, Tomas, Kai Chen, Greg Corrado, and Jeffrey Dean 2013 “Efficient Estimation of Word Representations in Vector Space.” In ICLR Workshop.Google Scholar), a neural network model that learns to detect semantically similar words based on their usage contexts (Firth 1957Firth, John Rupert 1957 “A Synopsis of Linguistic Theory 1930–1955. In Selected Papers of J.R. Firth 1952–1959, ed by. Frank Robert Palmer, 168–205. London: Longman.Google Scholar; Gries 2012Gries, Stefan Th 2012 “Behavioral Profiles: A Fine-grained and Quantitative Approach in Corpus-based Lexical Semantics.” In Methodological and Analytic Frontiers in Lexical Research, ed. by Gary Libben, Gonia Jarema, and Chris Westbury, 57–80. Amsterdam/Philadelphia: John Benjamins Publishing Company. CrossrefGoogle Scholar). We hypothesize that this grouping will also tie together similar expressions of affectivity and reveal the most typical ways of expressing affect in the tweets. Further, for each cluster, we estimate the 30 most typical tweets.

We extracted the tweets written in French based on the language identification offered by Twitter and excluded retweets and tweets without any linguistic information from the data. This gave us the final dataset, which consisted of 108,236 tweets.

Before the clustering, the tweets were preprocessed with UDPipe (Straka and Strakovà 2017Straka, Milan, and Jana Straková 2017 “Tokenizing, POS Tagging, Lemmatizing and Parsing UD 2.0 with UDPipe.” In Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, 88–99. Vancouver, Canada: Association for Computational Linguistics. CrossrefGoogle Scholar) to obtain morphological and syntactic information on the data. As a second step, we excluded tokens belonging to part-of-speech classes with little linguistic content, namely adpositions, determiners, punctuation, numbers, conjunctions, auxiliary verbs, and symbols, from the tweets. After this, the tweets were vectorized using the French word2vec embeddings published by Ginter et al. (2017)Ginter, Filip, Jan, Hajič, Juhani, Luotolahti, Milan Straka, and Daniel, Zeman 2017CoNLL 2017 Shared Task – Automatically Annotated Raw Texts and Word Embeddings. Prague: Charles University, LINDAT/CLARIN Digital Library at the Institute of Formal and Applied Linguistics (ÚFAL), Faculty of Mathematics and Physics. http://​hdl​.handle​.net​/11234​/1​-1989. To obtain vectors for whole tweets instead of individual words, we counted the average vectors from the word vectors belonging to the tweet. The clustering was done with KMeans Minibatch in Scikit learn. Different clustering solutions were compared, and the solution with 15 clusters using Euclidian distance was estimated as the best. Out of the 15 clusters, several clusters contained tweets that were posted to point out a link to a website, such as news events that unfolded. All these were excluded, and for the analysis, we kept eight topical clusters, with a total of 240 tweets. The topics found in these clusters were similar to those found in previous studies, which confirms our approach (Johansson et al. 2018Johansson, Marjut, Aki-Juhani Kyröläinen, Filip Ginter, Lotta Lehti, Attila Krizsán, and Veronika Laippala 2018 ”Opening Up #jesuisCharlie Anatomy of a Twitter Discussion With Mixed Methods.” Journal of Pragmatics 129: 90–101. CrossrefGoogle Scholar; Smyrnaios and Ratinaud 2017Smyrnaios, Nikos, and Pierre Ratinaud 2017 “The Charlie Hebdo Attacks on Twitter: A Comparative Analysis of a Political Controversy in English and French.” Social Media + Society 3 (1): 1–13. CrossrefGoogle Scholar). Here, we focus on the affectivity expressed in tweets in these clusters.

4.2Qualitative analysis

In the qualitative phase, we analyzed the 240 tweets22.We use tweets as such without any lexical or grammatical correction. that were included in the clusters and their expressions of affectivity.

The study of affect and emotions has to be considered on the three following levels: social and cultural practice (macrolevel), interactional practice of joint action (mesolevel), and language use and communicative acts in tweets (microlevel). At the microlevel, our analysis consisted of linguistic analysis of affectivity. It was studied regarding lexicogrammatical elements in terms of signaling or denoting emotions in the stances expressed by users (Bednarek 2008Bednarek, Monika 2008Emotion Talk Across Corpora. Basingstoke England, New York: Palgrave Macmillan. CrossrefGoogle Scholar; Du Bois 2007Du Bois, John 2007 “The Stance Triangle.” In Stancetaking in Discourse. Subjectivity, Evaluation and Interaction, ed. by Robert Englbretson, 139–182. Amsterdam/Philadelphia: John Benjamins Publishing Company. CrossrefGoogle Scholar, 163). At the mesolevel, we focused on how the users positioned themselves, and we analyzed the tweets as O-side or S-side assessments (Edwards and Potter 2017Edwards, Derek, and Jonathan Potter 2017 “Some Uses of Subject-side Assessments.” Discourse Studies 19 (5): 497–514. CrossrefGoogle Scholar). In addition, we studied whether the participants aligned or disaligned themselves with others (Du Bois 2007Du Bois, John 2007 “The Stance Triangle.” In Stancetaking in Discourse. Subjectivity, Evaluation and Interaction, ed. by Robert Englbretson, 139–182. Amsterdam/Philadelphia: John Benjamins Publishing Company. CrossrefGoogle Scholar, 163). In this analysis, we distinguished between individual and collective emotions. At the macrolevel, we studied what kind of we-agency was expressed (Salmela and Nagatsu 2017Salmela, Mikko, and Nagatsu, Michiru 2017 “How Does It Really Feel to Act Together? Shared Emotions and The Phenomenology of We-Agency”. Phenomenology and the Cognitive Sciences 16, 449–470. CrossrefGoogle Scholar) and what kind of shared values and togetherness or awayness belonged to this experience (Section 5). We then focused on tweets in which users departed from the we-agency and the group belonging and what kind of affectivity and values were expressed (Section 6). In the end, we analyzed tweets that consisted of negative affectivity towards the we-agency and shared values (Section 7.)

5.We-agency: Shared emotions, values, and identification

5.1Solidarity and grief

In the previous studies (see Section 2), solidarity and freedom of speech were found to be the most common expressions during this event. We will explore this further in French-speaking tweets in order to consider how it forms what we call we-agency (Salmela and Nagatsu 2017Salmela, Mikko, and Nagatsu, Michiru 2017 “How Does It Really Feel to Act Together? Shared Emotions and The Phenomenology of We-Agency”. Phenomenology and the Cognitive Sciences 16, 449–470. CrossrefGoogle Scholar). In the tweets that belong to this category, the participants shared their commitment through the hashtag #jesuisCharlie, especially identifying themselves as Charlie:

(1)

Chez nous, on est Charlie depuis Hara Kiri ! #JeSuisCharlie [link]

Here [at our place] [we are] Charlie since Hara Kiri!33.predecessor of Charlie Hebdo. #IamCharlie [link]

(2)

Je suis encore et toujours Charlie #jesuisCharlie

I am still and always Charlie #IamCharlie

In Examples (1) and (2), the tweeters identify themselves as Charlie by giving the index of time (depuis, since; encore et toujours, still and always). These tweets are S-side assessments in which the subjectivity is either individual (ex. (2)) or collective (ex. (1)). In Example (1), the stance is expressed through the personal pronoun nous (we) with a preposition (chez, at) indexing a local place, followed by an impersonal pronoun (on, we) that is inclusive of the writer. In Example (2), the participant uses the structure je suis (I am) to accentuate his/her commitment to Charlie. These are the kind of tweets which create bonds between networked users, creating what Ahmed calls towardness (Ahmed 2015Ahmed, Sara 2015The Cultural Politics of Emotion. Routledge, New York & London.Google Scholar, 8–9).

The participants expressed their support for solidarity and freedom of speech:

(3)

Etre Charlie, c’est defender les valeurs de liberté d’opinion et d’expression. Qui ne s’y revendique pas? Soyez Charlie ! #jesuisCharlie

To be Charlie, is to defend the values of freedom of opinion and speech. Who does not claim this? Be Charlie! #IamCharlie

(4)

PARIS EST CHARLIE #JesuisCharlie #QueLeurAmeReposeEnPaix #VivelaFrance #ViveCharlie #CharlieHEbdo [link]

PARIS IS CHARLIE #IamCharlie #MayTheirSoulRestInPeace #LongLiveFrance #LongliveCharlie #CharlieHebdo [link]

In Examples (3)–(4), the stances are not subjective, although the writers are evaluating Charlie; rather, they represent O-side assessments. In Example (3), the meaning of “To be Charlie” is spelled out by this participant, followed by a negative rhetorical question (Qui ne s’y revendique pas? Who does not claim this?) that presupposes that all participants in this Twitter discussion are identifying with Charlie. At the end of this tweet, there is a communicative act – an order – that boosts the rhetorical question (Soyez Charlie! Be Charlie!). Thus, identification is strongly invited by this participant. In Example (4), the identification is performed collectively, equating Paris with Charlie (Paris est Charlie, Paris is Charlie) and cheering on Charlie (Vive Charlie, Long live Charlie). The affect here is sharing emotions with people who feel the same according to these participants.

The participants also expressed their sorrow and mourning toward the victims.

(5)

#MarcheRepublicaine #JeSuisCharlie J’y serais en mémoire de toutes ces vies perdues. En hommage à tout ces anges. [link]

#Republican march #IamCharlie I will be there in memory of all these lost lives. Paying homage to all of these angels.

(6)

Dites moi que c’était juste un cauchemar, une blague et qu’on va tous se mettre à rire fort. #JeSuisCharlie

Tell me it was just a nightmare, a joke and that we are all going to laugh loudly. #IamCharlie

The Examples (5) and (6) are S-side assessments: there is a subjective stance expressed with the first-person pronoun (je, I and moi, me), and in 6, there is an inclusive impersonal pronoun on (we). In Example (5), the participant addresses the message toward the victims (vie perdus, lost lives), which is the object of her/his emotion (en mémoire de, homage; in the memory of, paying homage). Another hashtag, #MarcheRepublicaine, is used, where this writer announces she/he will be attending, J’y serais (I will be there). In Example (6), the participant signals disbelief (cauchemar, nightmare).

In the following examples, the affectivity is about shared values:

(7)

Des De les gens brandissent leur crayon en signe de soutien suite à l’attentat de Paris. #jesuischarlie #SOTU

People wave their pencils as a sign of support following the Paris attack. #IamCharlie #SOTU44.State of the union.

(8)

La marseillaise! #marseillaise #france #paris #marcherépublicaine #jesuisCharlie #dimanche #11 janvier [link]

La marseillaise!55.French national anthem. #marseillaise #france #paris #republican march #IamCharlie #Sunday #January 11 [link]

(9)

Dimanche j’étais vraiment fier d’être français! Tant de personnes ont dit NON à la barbarie et OUI à la liberté #JeSuisCharlie

Sunday I was really proud of being French! So many people said NO to barbarism and YES to liberty. #IamCharlie

(10)

Putain. Tous ensemble. Allez là #MarcheRépublicaine #JesuisCharlie

Fuck. All together. Go there #RepublicanWalk #IamCharlie

In Examples (7)–(10), the shared values – freedom of speech and solidarity – are the evaluative content of these tweets. They are O-side assessments, except for Example (9), and they take objects from national pride. In Example (7), the pen as a sign of freedom of speech is evoked, and in Example (8), there is mention of the French national anthem, the Marseillaise. In (9), the participant uses a first-person pronoun (j’étais, I was), with the adjective fier (proud) and the mention of nationality (Français, French). This emotion expresses this writer’s evaluation of a solidarity march and group belonging. In Example (10), there is an invitation: this participant uses a swearword at the beginning of her/his tweet (putain, fuck), thus signaling an emotion. He/she encourages all the tweeters to participate in the solidarity march.

In these examples, the social actors express affect that constitutes the core of the affectivity in this Twitter discussion. Participants share similar emotions that reveal shared values, primarily involving identifying with Charlie and manifesting group belonging. The participants are aware of one another’s positioning as they invite others to join and share the same emotions and values; thus, they align with each other. In this sense, participation in this large-scale Twitter discussion is a joint activity. The participants’ positioning shows moral values that are behind this strong manifestation of affect. However, most of these tweets in this section do not denote an emotion by naming it; instead, they signal them (cf. Bednarek 2008Bednarek, Monika 2008Emotion Talk Across Corpora. Basingstoke England, New York: Palgrave Macmillan. CrossrefGoogle Scholar). The values not only comprise defending freedom of speech, but they also include defending democratic and national values, which are the values that create towardness. The tweets constitute the we-agency (Salmela and Nagatsu 2017Salmela, Mikko, and Nagatsu, Michiru 2017 “How Does It Really Feel to Act Together? Shared Emotions and The Phenomenology of We-Agency”. Phenomenology and the Cognitive Sciences 16, 449–470. CrossrefGoogle Scholar) and togetherness (Ahmed 2015Ahmed, Sara 2015The Cultural Politics of Emotion. Routledge, New York & London.Google Scholar).

6.The limits of group belonging

6.1Shared values and anger against the other

There are tweets that express similar shared emotions and shared values as those analyzed in Section 5.1., but here, participants make the distinction between self and others manifested in S-side assessments. In other words, these types of tweets contain material in which social actors observe behaviors that are deviant from a straightforward commitment to the emotional content.

(11)

#JesuisCharlie pour la liberté d’expression pas du de le terrorisme !!!! #JesuisCharlie

# IamCharlie for the freedom of speech not for terrorism!!!! #IamCharlie

(12)

Il faut laîciser plus encore la République, sinon les religions nous embarqueront dans leur chantage à l’amour et à la haine. #jesuisCharlie

[There is a need to] make the Republic even more precise, otherwise the religions will embark us in their blackmail to love and hatred #IamCharlie

(13)

Encore sous le #choc! Je m’exprime peu sur les sujets à chaud, mais ne rien dire c’est laisser gagner ces malades! #JeSuisCharlie #Liberté

Still in #shock! I am expressing myself a little bit hastily about this topic, but to say nothing is to let these sick people win! #IamCharlie #Liberty

(14)

#JeSuisCharlie Je suis Charlie, mais je suis moi aussi. Focalisez vous plus sur le futur. On n’a pas fini avec le terrorisme malheureusement

#IamCharlie I am Charlie, but I am me too. Focus more on the future. We haven’t finished with terrorism unfortunately

In Examples (11)–(14), the participants align themselves with shared emotions and values (freedom of speech, republic, liberty, future). In Example (11), the writer distinguishes between freedom of speech and terrorism, whereas in 12, the participant takes national values (la république, republic) as her/his object of evaluation and points out what she/he considers to be the threat to it (religions). In other words, these social actors point out the we-agency and togetherness (ex. (10)), but they also illustrate its boundaries: terrorism, religion, and sick people (the other). In other words, from the social and cultural perspective, there is towardness, but it is signaled explicitly by what breaks the bond. These Examples (11)–(14) are S-side assessments in which the participants refer to themselves either by repeating the hashtag #jesuisCharlie or employing other first-person expressions in the singular or plural. In Examples (12) and (13), the participants denote their emotions clearly, amour, haine, and choc (love, hate, and shock).

In the last example in this section, the tweet is similar to those in which the writers engage in self-identification. However, like in the Examples (11)–(14), here, the other is also pointed out. The other is the enemy:

(15)

@[nom] @ [nom] [nom] Liberté d’expression !!! #JesuisCharlie #JesuisLibre #MaisjesuisPas MarineLaPute

@[name] @ [name] [name] Freedom of speech !!! #IamCharlie # IamFree #ButIamNot MarineTheBitch 66.reference to Marine Le Pen, extreme right wing politician of Front National in France.

In Example (15), there is an expression of shared values (liberté d’expression, freedom of speech) and that the writer is free (libre), but at the end of the tweet, he/she points to the political enemy, right-wing politician Marine LePen.

In these cases, the core of shared emotions is quite strong – they are comparable to the previous case, as are the values expressed here. They express themselves in S-side assessments identifying or supporting Charlie and the values that they associate with this publication or the event. However, the participants take different positions: they signal disalignment with others or other ideologies. Therefore, the affectivity that emerges, in addition to solidarity, freedom of speech, and commitment, is that of anger and hatred targeting what the other represents and threats to the values the participants want to claim. It expresses strong awayness from the other who does not support these values.

6.2Distancing from group belonging: Doubts and irony

There are tweets in which the participants share the same values but at the same time blame the other for not maintaining the shared emotions and values. In this respect, they point out explicitly the awayness they have observed (Ahmed 2015Ahmed, Sara 2015The Cultural Politics of Emotion. Routledge, New York & London.Google Scholar, 8–9). They are critical about maintaining the togetherness and are sad that it is breaking up, as in the following example:

(16)

Et sinon ya encore des de les gens qui sont Charlie ? Ou c’était juste de passage pour faire comme tous le monde ?! #JeSuisCharlie

And are there still people who are Charlie? Or was it just a passing moment to do like everyone else?! #IamCharlie

(17)

JeSuisCharlie la belle unité n aura pas duré longtemps… Marre de voir mon pays se déchirer

IamCharlie the beautiful unity did not last long… Sick of seeing my country breaking

The Example (16) is an O-side assessment, while the Example (17) is an S-side assessment. In Example (16), the participant asks two rhetorical questions in which he/she wonders about people’s commitment. He/she indexes time, encore (still) and de passage (momentary), signaling the passing of this momentary towardness and engagement in the shared values. The core identification and group belonging are at stake here – qui sont Charlie (who are Charlie). In Example (17), the participant complains and explicitly denotes an emotion (marre, sick). He/she complains that the togetherness of shared emotions and shared values did not last long (n aura pas duré longtemps, did not last long). He/she refers to the shared values by indicating la belle unite (beautiful unity) and referring to his/her country (mon pays, my country).

There are also participants who do not accept the core identification and group belonging:

(18)

Faut arrêter avec vos #JeSuisCharlie, #JaiMonCharlie Perso je m’appelle pas Charlie, mais on est tous français par contre donc… #Basta

Stop with your #IamCharlie, #IhaveMyCharlie Personally my name is not Charlie but on the other hand we are all French so… #Basta [Enough]

(19)

#JenesuispasCharlie ou #jesuisCharlie ! Bien dit #twittoma [link]

#IamNotCharlie or #IamCharlie! Well said #twittoma77. https://​Twittoma​.com is destined to Moroccans in Twitter. [link]

(20)

#JeSuisAhmed #JeSuisKouachi #JeSuisCharlie voilà comme ça quoi qu’il arrive j’ suis sûr d’ être dans le bon camp

#IamAhmed #IamKouachi #IamCharlie there whatever happens I am sure I’m in the right camp

In Example (18), S-side assessment, this participant does not accept the core identification: he/she initially denies this by expressing an order to those who commit to it (Faut arrêter avec vos #JeSuisCharlie, Stop with your #IamCharlie). Although he/she denies of being Charlie (je m’appelle pas Charlie, my name is not Charlie), he/she commits to the shared values by indicating nationality with the use of inclusive on (we; on est tous français, we are all French). The Example (19) is an O-side assessment in which the user weighs if one should be Charlie with the construction je suis (I am). However, in Example (20), all the utterances build an S-side assessment and allows the participant to be ironical. He/she enumerates three hashtags in the beginning of the tweet that name the killed police officer (Ahmed), the perpetrators (Kouachi), and Charlie and identifies with them all (comme ça quoi qu’il arrive j’ suis sûr d’ être dans le bon camp, whatever happens I am sure I’m in the right camp). Here, there is no marking of the shared emotions or the shared values. In sum, the participants express their doubts and ironical stance against the others who do not share the same emotions by signaling the emotion; none of them denote emotions explicitly.

7.Threats to shared values

7.1Irritation, anger, and repulsion

Some of the tweeters considered that not everyone shares the same values, and thus, they threaten democracy and togetherness. They tweet about the awayness (Ahmed 2015Ahmed, Sara 2015The Cultural Politics of Emotion. Routledge, New York & London.Google Scholar, 8–9). Their tweets are othering: the persons who take as the objects of their emotion by which they express their concerns (Salmela and Nagatsu 2017Salmela, Mikko, and Nagatsu, Michiru 2017 “How Does It Really Feel to Act Together? Shared Emotions and The Phenomenology of We-Agency”. Phenomenology and the Cognitive Sciences 16, 449–470. CrossrefGoogle Scholar, 457). Especially, they consider that freedom of speech is not shared by politicians; if it was, they should be talking about it in relation to other matters as well:

(21)

Hé les politiciens qui surfaient sur la vague de #jesuisCharlie ! C’est le temps d’agir pour la liberté d’expression #JesuisRaif88.Raïf Badawi is a Saudi activist and writer.

Hey the politicians who were surfing the #IamCharlie wave! It is time to act for freedom of speech #IamRaif

(22)

Liberté d’expresson jusqu’où ? #JesuisCharlie #Dieudonné [link]

Freedom of expression until where? #IamCharlie #Dieudonné99.Dieudonné, Dieudonné M’bala M’bala, a French political activist, actor and comedian who was accused and convicted from hate speech and advocating terrorism and slander. [link]

(23)

Émotions chez @michelonfray : c’est vrai q’ on n’a pas fait d’analyse politique après le 7janvier: tu m’étonnes ?! #JeSuisCharlie #ONPC

Emotions at @michelonfray:1010.Michel Onfray, a French philosopher, known for his anarchism and atheism. it is true that we haven’t done a political analysis after the 7th of January: you surprise me? #IamCharlie #ONPC1111.Talk show on French TV channel France2.

In Examples (21)–(23), O-side assessments, the participants comment on the ongoing discussion across media while mentioning either political figures (Raïf, Dieudonné) or a philosopher (Michel Onfray). In Example (21), this participant invites others to action for another cause; in Example (22), there is a rhetorical question about the limits of freedom of speech, and, actually, this tweet can be interpreted as being against hate speech. In Example (23), the participant notes the emotions the philosopher has expressed, aligning with it questioning of others’ surprise (tu m’étonnes, you surprise me). They observe the awayness of the moment that united users together.

There are tweets that involve disalignment from the political ideologies in France or French politics:

(24)

J’ai encore plus mal à ma France depuis l’attentat #CharlieHebdo #envoyespecial je ne fais plus confiance la gauche m’a tué #JeSuisCharlie

I am even more sick for my France since the attack #CharlieHebdo #envoyé special1212.TV show that broadcasts reports about social issues and stories from abroad. I don’t trust anymore the left killed me #IamCharlie

(25)

François Hollande se cache derrière #jesuisCharlie manifestation pacifique mondiale dont il n’est pas l’initiateur et fais sa politique de merde

François Hollande1313.French president François Hollande (Socialist party) at the time of the attack. hides behind #IamCharlie worldwide peaceful demonstration of which he is not the initiator and he makes his damn politics

Example (24) is one of the clearest examples of S-side assessments that contains a denoted emotion. The participant expresses the affect from his/her point of view with utterances with je (I) that express his/her malaise (encore plus mal, even more sick) and distrust (je ne fais plus confiance, I don’t trust anymore) of the French political left. The socialist politics are also under attack in Example (25), where the participant bashes the president at the time, François Hollande, in an O-side assessment. Here, there is an expression of anger and repulsion (politique de merde, his damn politics). In other words, the affectivity is turned against those who do not contribute to the togetherness or we-agency but instead fake it or eat away at it.

7.2Disgrace and condemnation

In the last set of examples, the social actors express feelings of disgrace about three different elements linked with this event:

(26)

Comment un humain, qu’importe sa religion ou sa couleur, peut-il dire “ils sont morts bien fait” Honteux! #Jesuischarlie = Liberté d’exp.

How is a man able to say, despite of his religion or his color, “they died well” What a disgrace! #IamCharlie=Freedom of speech

(27)

Honteaux à les #médias qui n’ont pas consacré une seconde à l’attentat du de le groupe islamiste #BokoHaram au à le Nigéria. #JeSuisCharlie

Shame on the #media who didn’t dedicate a second for the attack of the Islamist group #BokoHaram in Nigeria. #IamCharlie

(28)

#jesuisRaif #jesuisCharlie 7000 mille ans d’histoire parties en fumée grâce à Daesh…les nazis n’ont pas fair mieux [link]

#IamRaif #IamCharlie 7000 thousand years of history up in smoke thanks to Isis… the Nazis did not do better [link]

In Examples (26) and (27), the emotion is denoted as disgrace (honte, honteux) in O-side assessments. In (26), the writer condemns the inappropriate opinions of their co-participants. In (27), the writer is indignant that the media has not covered a similar, poignant news event that has taken place in Africa. In both tweets, the repulsion is about an observation of clear offense against the shared value of freedom of speech. These social actors disalign from those who have transgressed this value. In the last Example (28), an O-side assessment, the participant condemns ISIS, accusing them of destroying the past and comparing them with the Nazis. They condemn the kind of behaviors that create awayness and violate most clearly the core of democratic values of the we-agency and togetherness.

8.Discussion and conclusion

The emotions expressed in the French-language Twitter discussion on #jesuisCharlie can be divided into two categories according to the type of emotions and how participants positioned themselves.

First, the participants expressed emotions and values that built togetherness and towardness. These emotions were expressed by sharing the identification with Charlie and defending the freedom of speech with all the other participants, on the one hand, and expressing grief and condolences on the other. These expressions were mostly S-side assessments in which participants build identification with the construction je suis (I am). As for O-side assessments, the participants used them to refer to freedom of speech. In addition, references to democratic and republican values, as well as disbelief, were brought up in both types of assessments. In sum, the togetherness and the towardness expressed in these types of tweets built up a situated we-agency (Salmela and Nagatsu 2017Salmela, Mikko, and Nagatsu, Michiru 2017 “How Does It Really Feel to Act Together? Shared Emotions and The Phenomenology of We-Agency”. Phenomenology and the Cognitive Sciences 16, 449–470. CrossrefGoogle Scholar). These emotions and what they evaluated constituted the affective core of this Twitter discussion in French, demonstrating shared values and the participants’ alignment with them. The participants were aware of one another’s emotions, and they invited others to join to make the same kind of commitment.

Second, as #jesuisCharlie was a networked discussion with large-scale participation, the towardness and the togetherness did not last nor hold in every respect. In some cases, even though social actors shared the above mentioned emotions, participants needed to signal the limits of group belonging and the values that were at stake. These tweets contained both types of assessments. O-side assessments were particularly used to express anger and hatred against those who broke the values. Then, participants expressed their doubts and ironical stance against the ecstatic sharing (Giaxoglou 2018Giaxoglou, Korina 2018 “JeSuisCharlie? Hashtags as Narrative Resources in Contexts of Ecstatic Sharing.” Discourse, Context & Media 22: 13–20. CrossrefGoogle Scholar), thereby disaligning themselves from the collective commitment. They did not want to engage themselves with the we-agency and were skeptical and ironic. When users were evaluating opinions and views that had been expressed in the media by politicians or other known figures, the emotions became very negative in the form of irritation, anger, and repulsion regarding the wrong kinds of actions these media persons had taken. This showed distrust against all who violated the togetherness and democratic values.

Acknowledgements

We thank PhD Kaiju Harinen and MA Jenna Saarni for their help in the analysis. They worked as assistants at different phases of the analysis.

Notes

1.Collected by Marco T. Bastos and Raquel Recuero.
2.We use tweets as such without any lexical or grammatical correction.
3.predecessor of Charlie Hebdo.
4.State of the union.
5.French national anthem.
6.reference to Marine Le Pen, extreme right wing politician of Front National in France.
7. https://​Twittoma​.com is destined to Moroccans in Twitter.
8.Raïf Badawi is a Saudi activist and writer.
9.Dieudonné, Dieudonné M’bala M’bala, a French political activist, actor and comedian who was accused and convicted from hate speech and advocating terrorism and slander.
10.Michel Onfray, a French philosopher, known for his anarchism and atheism.
11.Talk show on French TV channel France2.
12.TV show that broadcasts reports about social issues and stories from abroad.
13.French president François Hollande (Socialist party) at the time of the attack.

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Address for correspondence

Marjut Johansson

School of Languages and Translation Studies

University of Turku

Koskenniemenkatu 4

20014

Finland

marjut.johansson@utu.fi

Biographical notes

Marjut Johansson is Professor at the Department of French Studies, at the School of Languages and Translation Studies, University of Turku. Her most recent topic focuses on interaction that is based on artificial intelligence, such as chatbots and robot-human interaction. Her other recent work covers topics on digital interaction and discourse and it includes work that examines online news discourse, social media, Twitter and discussion forum discussions, and videos. She is also interested in multimodal, digital humanities, and mixed method approaches.

Veronika Laippala is Associate professor in Digital Linguistics at the School of Languages and Translation Studies at the University of Turku, Finland. Her current research focuses on online language use and the study of registers in the multilingual Internet, in particular using very large corpora and computational methods. Her research has been published in peer-reviewed journals, such as Corpus linguistics and linguistic theory and Journal of pragmatics.