Cover not available
Article published In:
Linguistic Recycling: The process of quoting in increasingly mediatized settings
Edited by Lauri Haapanen and Daniel Perrin
[AILA Review 33] 2020
► pp. 67–85

Recycling a genre for news automation

The production of Valtteri the Election Bot

| University of Jyväskylä
| University of Helsinki
The amount of available digital data is increasing at a tremendous rate. These data, however, are of limited use unless converted into a user-friendly form. We took on this task and built a natural language generation (NLG) driven system that generates journalistic news stories about elections without human intervention. In this paper, after presenting an overview of state-of-the-art technologies in NLG, we explain systematically how we identified and then recontextualized the determinant aspects of the genre of an online news story in the algorithm of our NLG software. In the discussion, we introduce the key results of a user test we carried out and some improvements that these results suggest. Then, after relating the news items that our NLG system generates to general aspects of genres and their evolution, we conclude by questioning the idea that journalistic NLG systems should mimic journalism written by humans. Instead, we suggest that developmental work in the field of news automation should aim to create a new genre based on the inherent strengths of NLG. Finally, we present a few suggestions as to what this genre could include.
Keywords: news automation, natural language generation, NLG, genre, journalism
Article outline
  • 1.Introduction: Converting large data sets into user-friendly form
  • 2.State-of-the-art in NLG: A spectrum from ruled-based to training-driven methods
  • 3.Case study: The production of Valtteri the Election Bot
    • 3.1Domain selection: Topicality and relevance
    • 3.2Document planning: Readers’ preferences, news values, and rhetorical structures
    • 3.3Microplanning: Lexicalization and aggregation
    • 3.4Realization: Orthography and typography
  • 4.Discussion: Toward a distinctive genre of online news story
    • 4.1Challenge: Trade-offs to improve Valtteri’s performance
    • 4.2Solution: From non-typicality to a new genre
  • 5.Conclusion
  • Notes
  • References
Available under the Creative Commons Attribution-NonCommercial (CC BY-NC) 4.0 license.

For any use beyond this license, please contact the publisher at [email protected].

Published online: 7 October 2020
DOI logo
https://doi.org/10.1075/aila.00030.haa
References (34)
References
Beckett, C. (2019). New powers, new responsibilities. A global survey of journalism and artificial intelligence. The Journalism AI. Retrieved from <[URL]> (22 February, 2020).
Chandola, V., Banerjee, A., & Kumar, V. (2009). Anomaly detection: A survey. ACM Computing Surveys, 41(3), 151:1–15:58. DOI logoGoogle Scholar
Clerwall, C. (2014). Enter the robot journalist: Users’ perceptions of automated content. Journalism Practice, 8(5), 519–531. DOI logoGoogle Scholar
Devitt, A. J. (2004). Writing genres. Carbondale, IL: Southern Illinois University Press.Google Scholar
Diakopoulos, N. (2019). Automating the news. How algorithms are rewriting the media. Cambridge, MA: Harvard University Press. DOI logoGoogle Scholar
Fairclough, N. (1992). Discourse and social change. Cambridge: Polity Press.Google Scholar
Gatt, A., & Krahmer, E. (2017). Survey of the state of the art in natural language generation: Core tasks, applications and evaluation. Journal of Artificial Intelligence Research, 601, 75–170.Google Scholar
Graefe, A., Haim, M., Haarmann, B., & Brosius, H.-B. (2016). Readers’ perception of computer-generated news: Credibility, expertise, and readability. Journalism, 19(5), 595–610. DOI logoGoogle Scholar
Gupta, M., Gao, J., Aggarwal, C. C., & Han, J. (2014). Outlier detection for temporal data: A survey. IEEE Transactions on Knowledge and Data Engineering, 26(9), 2250–2267. DOI logoGoogle Scholar
Hansen, M., Roca-Sales, M., Keegan, J. M., & King, G. (2017). Artificial intelligence: Practice and implications for journalism. Columbia University Academic Commons. DOI logoGoogle Scholar
Kim, D. & Lee, J. (2019). Designing an algorithm-driven text generation system for personalized and interactive news reading. International Journal of Human–Computer Interaction, 35(2), 109–122. DOI logoGoogle Scholar
Latar, N. L. (2015). The robot journalist in the age of social physics: The end of human journalism? In G. Einav (Ed.), The new world of transitioned media: Digital realignment and industry transformation (pp. 65–80). Wiesbaden: Springer. DOI logoGoogle Scholar
Lee, A. M. (2014). How fast is too fast? Examining the impact of speed-driven journalism on news production and audience reception (Unpublished doctoral dissertation). The University of Texas at Austin.Google Scholar
Leppänen, L., Munezero, M., Granroth-Wilding, M., & Toivonen, H. (2017a). Data-driven news generation for automated journalism. In Proceedings of the 10th International Conference on Natural Language Generation, 188–197. DOI logoGoogle Scholar
Leppänen, L., Munezero, M., Sirén-Heikel, S., Granroth-Wilding, M., & Toivonen, H. (2017b). Finding and expressing news from structured data. In Proceedings of the 21st International Academic Mindtrek Conference, 174–183. DOI logoGoogle Scholar
Lindén, C.-G. (2017). Decades of automation in the newsroom: Why are there still so many jobs in journalism? Digital Journalism, 5(2), 123–140. DOI logoGoogle Scholar
Lindén, C.-G., & Tuulonen, H. (Eds.) together with Bäck, A., Diakopoulos, N., Haapanen, L., Leppänen, L., Melin, M., Munezero, M., Sirén-Heikel, S., Södergård, C., & Toivonen, H. (2019). News Automation: The rewards, risks and realities of “machine journalism”. WAN-IFRA guide to the field. Reports / The World Association of Newspapers and News Publishers WAN-IFRA.Google Scholar
Luginbühl, M. (2014). Genre profiles and genre change: The case of TV news. In J. Androutsopoulos (Ed.), Mediatization and Sociolinguistic Change (pp. 305–330). Berlin, New York: de Gruyter. DOI logoGoogle Scholar
Martin, J. R. (1985). Process and text: two aspects of human semiosis. In J. D. Benson, & W. S. Greaves (Eds.), Systemic perspectives on discourse (pp. 248–274). Norwood, NJ: Ablex.Google Scholar
Melin, M., Bäck, A., Södergård, C., Munezero, M., Leppänen, L., & Toivonen, H. (2018). No landslide for the human journalist. An empirical study of computer-generated election news in Finland. IEEE Access, 61, 43356–43367. DOI logoGoogle Scholar
Miller, C. (1984). Genre as social action. Quarterly Journal of Speech 70(2), 151–167. DOI logoGoogle Scholar
Miller, C., & Shepherd, D. (2009). Questions for genre theory from the blogosphere. In J. Giltrow (ed.), Genres in the Internet: Issues in the theory of genre (pp. 264–286). Amsterdam: John Benjamins. DOI logoGoogle Scholar
Murphy, K. P. (2012). Machine learning: A probabilistic perspective. Cambridge, MA: The MIT press.Google Scholar
Mäntynen, A., & Shore, S. (2014). What is meant by hybridity? An investigation of hybridity and related terms in genre studies. Text and talk, 34(6), 737–758. DOI logoGoogle Scholar
O’Neill, D., & Harcup, T. (2009). News values and selectivity. In Wahl-Jorgensen, K. & Hanitzsch, T. (Eds.) Handbook of journalism studies (pp. 161–174). New York, NY: Routledge.Google Scholar
Pietikäinen, S., & Mäntynen, A. (2020). Uusi kurssi kohti diskurssia. Tampere: Vastapaino.Google Scholar
Pöttker, H. (2003). News and its communicative quality: the inverted pyramid – when and why did it appear? Journalism Studies, 4(4), 501–511. DOI logoGoogle Scholar
Rosenberg, H., & Feldman, C. S. (2008). No time to think: The menace of media speed and the 24-hour news cycle. New York, NY: Continuum.Google Scholar
Weaver, D. H., & Willnat, L. (Eds.). (2012). The global journalist in the 21st century. London: Routledge. DOI logoGoogle Scholar
Wölker, A., & Powell, T. E. (2018). Algorithms in the newsroom? News readers’ perceived credibility and selection of automated journalism. Journalism. DOI logoGoogle Scholar
Zampa, M. (2017). Argumentation in the newsroom. Amsterdam: John Benjamins. DOI logoGoogle Scholar
Sirén-Heikel, S., Leppänen, L., Lindén, C.-G., & Bäck, A. (2019). Unboxing news automation: Exploring imagined affordances of automation in news journalism. Nordic Journal of Media Studies 1(1), 47–66. DOI logoGoogle Scholar
Cited by (1)

Cited by one other publication

Haapanen, Lauri
2022. Adapting Media Self-Regulation to the Era of News Automation. In Futures of Journalism, ► pp. 81 ff. DOI logo

This list is based on CrossRef data as of 4 july 2024. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.