Developing a successful SemEval task in sentiment analysis of Twitter and other social media texts.
We present the development and evaluation of a semantic analysis task that lies at the intersection of two very trendy lines of research in contemporary computational linguistics: (1) sentiment analysis, and (2) natural language processing of social media text. The task was part of SemEval, the Inte...
| Publicado en: | Language Resources & Evaluation Vol. 50; no. 1; pp. 35 - 66 |
|---|---|
| Autores principales: | , , , , , , , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Mar2016
|
| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=113139628&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 113139628 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Mar2016 vid: 50 iid: 1 pid: 237 pub: Springer Nature artinfo: ui: 113139628 10.1007/s10579-015-9328-1 ppf: 35 ppct: 31 formats: fmt: @attributes: type: P size: 933KB tig: atl: Developing a successful SemEval task in sentiment analysis of Twitter and other social media texts. aug: au: Nakov, Preslav Rosenthal, Sara Kiritchenko, Svetlana Mohammad, Saif Kozareva, Zornitsa Ritter, Alan Stoyanov, Veselin Zhu, Xiaodan affil: Qatar Computing Research Institute, HBKU, Tornado Tower, floor 10 Doha Qatar Columbia University, New York USA National Research Council Canada, 1200 Montreal Rd. Ottawa Canada USC Information Sciences Institute, 4676 Admiralty Way Marina del Rey 90292-6695 USA The Ohio State University, Columbus USA Johns Hopkins University, Baltimore USA su: Sentiment analysis Computational linguistics Natural language processing Semantics Microblogs Computer network resources sug: subj: Sentiment analysis Computational linguistics Natural language processing Semantics Microblogs Computer network resources keyword: SemEval ab: We present the development and evaluation of a semantic analysis task that lies at the intersection of two very trendy lines of research in contemporary computational linguistics: (1) sentiment analysis, and (2) natural language processing of social media text. The task was part of SemEval, the International Workshop on Semantic Evaluation, a semantic evaluation forum previously known as SensEval. The task ran in 2013 and 2014, attracting the highest number of participating teams at SemEval in both years, and there is an ongoing edition in 2015. The task included the creation of a large contextual and message-level polarity corpus consisting of tweets, SMS messages, LiveJournal messages, and a special test set of sarcastic tweets. The evaluation attracted 44 teams in 2013 and 46 in 2014, who used a variety of approaches. The best teams were able to outperform several baselines by sizable margins with improvement across the 2 years the task has been run. We hope that the long-lasting role of this task and the accompanying datasets will be to serve as a test bed for comparing different approaches, thus facilitating research. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2016. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2016 holdings: @attributes: islocal: N |
|---|