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Article published In:
The Dynamics of Lexical Innovation: Data, methods, models
Edited by Daphné Kerremans, Jelena Prokić, Quirin Würschinger and Hans-Jörg Schmid
[Pragmatics & Cognition 25:1] 2018
► pp. 174–200

Using data-mining to identify and study patterns in lexical innovation on the web

The NeoCrawler

| Ludwig-Maximilians-Universität München
| Ludwig-Maximilians-Universität München
| Ludwig-Maximilians-Universität München
| Ludwig-Maximilians-Universität München

This paper presents the NeoCrawler – a tailor-made webcrawler, which identifies and retrieves neologisms from the Internet and systematically monitors the use of detected neologisms on the web by means of weekly searches. It enables researchers to use the web as a corpus in order to investigate the dynamics of lexical innovation on a large-scale and systematic basis. The NeoCrawler represents an innovative web-mining tool which opens up new opportunities for linguists to tackle a number of unresolved and under-researched issues in the field of lexical innovation. This paper presents the design as well as the most important characteristics of two modules, the Discoverer and the Observer, with regard to the usage-based study of lexical innovation and diffusion.

Keywords: lexical innovation, neologisms, webcrawler, data-mining, string matching, innovation identification
Article outline
  • 1.Introduction
  • 2.The Discoverer
    • 2.1Source material and pre-processing
    • 2.2String matching procedure
    • 2.3Reference dictionary
    • 2.4Manual evaluation
  • 3.The Observer
    • 3.1Architecture of the Observer
    • 3.2The NeoCrawler database
    • 3.3The Observer interface
  • 4.Summary and future work
  • Notes
  • References
Published online: 12 June 2019
DOI logo
https://doi.org/10.1075/pc.00006.ker
References
Algeo, John
1998 Vocabulary. In Suzanne Romaine (ed.), The Cambridge history of the English Language, vol. 31, Cambridge: Cambridge University Press. 57–91.Google Scholar
Ayto, John
2003 Newspapers and neologisms. In Jean Aitchison & Diana M. Lewis (eds.), New media language, 182–187. Routledge: New York.Google Scholar
Baayen, Harald R. & Anneke Neijt
1997 Productivity in context: A case study of a Dutch suffix. Linguistics 351. 565–587. DOI logoGoogle Scholar
Bauer, Laurie
1983 English word-formation. Cambridge: Cambridge University Press. DOI logoGoogle Scholar
Cabré, Maria Teresa & Lluís de Yzaguirre
1995 Stratégie pour la détection semiautomatique des néologismes de presse. TTR: Traduction, Terminologie, Redaction 81. 89–100. DOI logoGoogle Scholar
Cartier, Emmanuel
2017 Neoveille, a web platform for neologism tracking. Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics, 95–98. DOI logoGoogle Scholar
2019 (to appear). Néoveille, plateforme de détection, de description et de suivi des néologismes en onze langues. Néologica.Google Scholar
Falk, Ingrid, Delphine Bernhard & Christophe Gérard
2018 The Logoscope: A semi-automatic tool for detecting and documenting French new words from the linguistic project to the web interface. Research Report, Université Strasbourg. [URL] [accessed 1 August 2018].
Fischer, Roswitha
1998 Lexical change in present-day English: A corpus-based study of the motivation, institutionalization, and productivity of creative neologisms. Tübingen: Narr.Google Scholar
Gérard, Christophe, Lauren Bruneau, Ingrid Falk, Delphine Bernhard & Ann-Lise Rosio
2017 Le Logoscope : Observatoire des innovations lexicales en français contemporain. In Joaquín García Palacios, Goedele de Sterck, Daniel Linder, Jesús Torre del Rey, Miguel Sánchez Ibanez & Nava Maroto García (eds.), La neología en las lenguas Románicas: Recursos, estrategias y nuevas orientaciones. Frankfurt: Peter Lang. 339–356.Google Scholar
Hamilton, William L., Jure Leskovec & Dan Jurafsky
2016 Cultural shift or linguistic drift? Comparing two computational models of semantic change. Proceedings of Conference on Empirical Methods on Natural Language Processing, Austin, Texas, USA, 1–5 November 2016. [URL] [accessed 1 March 2018]. DOI logo
Iakovleva, Tatiana
2017 Automatic detection of neologisms in Russian newspaper corpora with Néoveille. Proceedings of the International Conference CORPUS LINGUISTICS – 2017, St Petersburg, 27–30 June 2017, 43–47. [URL] [accessed 1 May 2018].
Janssen, Maarten
2005 NeoTrack: Semiautomatic neologism detection. APL Conference 2005, Lisboa, Portugal. [URL] [accessed 15 March 2018].
Jatowt, Adam & Kevin Duh
2014 A framework for analysing semantic change of words across time. Proceedings of the 14th ACM/IEEE-CS Joint Conference on Digital Libraries, 229–238. DOI logoGoogle Scholar
Kerremans, Daphné
2015 A web of new words: A corpus-based study of the conventionalization process of English neologisms. Frankfurt am Main: Peter Lang. DOI logoGoogle Scholar
Kerremans, Daphné, Susanne Stegmayr & Hans-Jörg Schmid
2012 The NeoCrawler: Identifying and retrieving neologisms from the internet and monitoring on-going change. In Kathryn Allan & Justyna Robinson (eds.), Current methods in historical semantics, 59–96. Berlin: Mouton de Gruyter.Google Scholar
Kerremans, Daphné & Jelena Prokić
2018 Mining the web for new words: Semi-automatic neologism identification with the NeoCrawler. Anglia 136(2). 239–268. DOI logoGoogle Scholar
Labov, William
1966 The social stratification of English in New York City. Washington: Center for Applied Linguistics.Google Scholar
1980 The social origins of sound change. In William Labov (ed.), Locating language in time and space, 251–266. New York: Academic Press.Google Scholar
2001 Principles of linguistic change. Volume II: Social factors. Oxford: Blackwell.Google Scholar
Levenshtein, Vladimir I.
1965 Binary codes capable of correcting deletions, insertions, and reversals. Soviet Physics Doklady 101. 707–710.Google Scholar
Lewandowski, Dirk
2008 A three-year study on the freshness of web search engine databases. Journal of Information Science 34(6). 817–831. DOI logoGoogle Scholar
Liao, Xuanyi & Guang Cheng
2016 Analysing the semantic change based on word embedding. In Natural language understanding and intelligent applications. Proceedings of the 5th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2016, and 24th International Conference on Computer Processing of Oriental Languages, ICCPOL 2016, Kunming, China, December 2–6, 2016, 213–223. Cham: Springer.Google Scholar
Liu, Tsun-Jui, Shu-Kai Hsieh & Laurent Prevot
2013 Observing features of PTT neologisms: A corpus-driven study with N-gram model. Proceedings of the Twenty-Fifth Conference on Computational Linguistics and Speech Processing (ROCLING 2013), 250–259.Google Scholar
Megerdoomian, Karine & Ali Hadjarian
2010 Mining and classification of neologisms in Persian blogs. Proceedings of the 2nd Workshop on Computational Approaches to Linguistic Creativity (HLT 2010), 6–13.Google Scholar
Milroy, James & Lesley Milroy
1985 Linguistic change, social network and speaker innovation. Journal of Linguistics 211. 339–384. DOI logoGoogle Scholar
Nevalainen, Terttu
2000 Mobility, social networks and language change in Early Modern England. European Journal of English Studies 4(3). 253–264. DOI logoGoogle Scholar
Nevalainen, Terttu & Helena Raumolin-Brunberg
2003 Historical sociolinguistics: Language change in Tudor and Stuart England. London: Longman.Google Scholar
Plag, Ingo
1999 Morphological productivity: Structural constraints in English derivation. Berlin/New York: Mouton de Gruyter. DOI logoGoogle Scholar
Säily, Tanja, Eetu Mäkelä & Mika Hämäläinen
2018 Explorations into the social contexts of neologism use in early English correspondence. Pragmatics & Cognition 25(1). 29–48. [=this volume] DOI logoGoogle Scholar
Schmid, Hans-Jörg
2016 English morphology and word-formation: An introduction, 3rd revised and extended edition. Berlin: Erich Schmidt.Google Scholar
Tagliamonte, Sali A. & Derek Denis
2014 Expanding the transmission/diffusion dichotomy: Evidence from Canada. Language 90(1). 90–136. DOI logoGoogle Scholar
Torres-del-Rey, Jesús & Nava Maroto
2014 Building the interface between experts and linguists in the detection and characterisation of neology in the field of neurosciences. Proceedings of the 4th International Workshop on Computational Terminology, Dublin, Ireland, August 2014, 64–67. [URL] [accessed 25 March 2018].
Tournier, Jean
1985 Introduction Descriptive à la Lexicogénétique de l’Anglais Contemporain. Paris: Champion-Slatkine.Google Scholar
Wilson, Lee
2017 Google Freshness Algorithm: Everything you need to know. Search Engine Journal. [URL]. Last accessed August 1, 2018.
Cited by

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Würschinger, Quirin
2021. Social Networks of Lexical Innovation. Investigating the Social Dynamics of Diffusion of Neologisms on Twitter. Frontiers in Artificial Intelligence 4 DOI logo

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