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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 13 of 13 1 Dependency Syntax in the Automatic Detection of Irony and Stance ; Sintaxis de dependencias en la detección automática de ironía y posicionamiento Cignarella, Alessandra Teresa. - : Sociedad Española para el Procesamiento del Lenguaje Natural, 2022 BASE Show details 2 A Multilingual Dataset for Named Entity Recognition, Entity Linking and Stance Detection in Historical Newspapers Hamdi, Ahmed; Linhares Pontes, Elvys; Boros, Emanuela... In: SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval ; https://hal.archives-ouvertes.fr/hal-03418387 ; SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Jul 2021, Virtual Event, Canada. pp.2328-2334, ⟨10.1145/3404835.3463255⟩ (2021) BASE Show details 3 Multilingual Dataset for Named Entity Recognition, Entity Linking and Stance Detection in Historical Newspapers ... Hamdi, Ahmed; Elvys Linhares Pontes; Boros, Emanuela. - : Zenodo, 2021 BASE Show details 4 Annotation Guidelines for Named Entity Recognition, Entity Linking and Stance Detection ... Hamdi, Ahmed; Elvys Linhares Pontes; Doucet, Antoine. - : Zenodo, 2021 BASE Show details 5 Multilingual Dataset for Named Entity Recognition, Entity Linking and Stance Detection in Historical Newspapers ... Hamdi, Ahmed; Elvys Linhares Pontes; Boros, Emanuela. - : Zenodo, 2021 BASE Show details 6 Annotation Guidelines for Named Entity Recognition, Entity Linking and Stance Detection ... Hamdi, Ahmed; Elvys Linhares Pontes; Doucet, Antoine. - : Zenodo, 2021 BASE Show details 7 HeadlineStanceChecker: Exploiting summarization to detect headline disinformation Sepúlveda-Torres, Robiert; Vicente, Marta; Saquete Boró, Estela. - : Elsevier, 2021 BASE Show details 8 Dependency Syntax in the Automatic Detection of Irony and Stance Cignarella, Alessandra Teresa. - : Universitat Politècnica de València, 2021 BASE Show details 9 Dialogical Signals of Stance Taking in Spontaneous Conversation Rolston, Leanne Elizabeth. - 2020 BASE Show details 10 #Brexit: Leave or Remain? The Role of User's Community and Diachronic Evolution on Stance Detection Lai, Mirko; Patti, Viviana; Ruffo, Giancarlo; Rosso, Paolo. - : IOS Press, 2020 Abstract: [EN] Interest has grown around the classification of stance that users assume within online debates in recent years. Stance has been usually addressed by considering users posts in isolation, while social studies highlight that social communities may contribute to influence users¿ opinion. Furthermore, stance should be studied in a diachronic perspective, since it could help to shed light on users¿ opinion shift dynamics that can be recorded during the debate. We analyzed the political discussion in UK about the BREXIT referendum on Twitter, proposing a novel approach and annotation schema for stance detection, with the main aim of investigating the role of features related to social network community and diachronic stance evolution. Classification experiments show that such features provide very useful clues for detecting stance. ; The work of P. Rosso was partially funded by the Spanish MICINN under the research projects MISMIS-FAKEnHATE on Misinformation and Miscommunication in social media: FAKE news and HATE speech(PGC2018-096212-B-C31) and PROMETEO/2019/121 (DeepPattern) of the Generalitat Valenciana. The work of V. Patti and G. Ruffo was partially funded by Progetto di Ateneo/CSP 2016 Immigrants, Hate and Prejudice in Social Media (S1618 L2 BOSC 01). ; Lai, M.; Patti, V.; Ruffo, G.; Rosso, P. (2020). #Brexit: Leave or Remain? The Role of User's Community and Diachronic Evolution on Stance Detection. Journal of Intelligent & Fuzzy Systems. 39(2):2341-2352. https://doi.org/10.3233/JIFS-179895 ; S ; 2341 ; 2352 ; 39 ; 2 ; Blondel, V. D., Guillaume, J.-L., Lambiotte, R., & Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008(10), P10008. doi:10.1088/1742-5468/2008/10/p10008 ; Deitrick, W., & Hu, W. (2013). Mutually Enhancing Community Detection and Sentiment Analysis on Twitter Networks. Journal of Data Analysis and Information Processing, 01(03), 19-29. doi:10.4236/jdaip.2013.13004 ; Duranti A. and Goodwin C. , Rethinking context: Language as an interactive phenomenon, Cambridge University Press, (1992). ; Evans A. , Stance and identity in Twitter hashtags, Language@ Internet 13(1) (2016). ; Fortunato, S. (2010). Community detection in graphs. Physics Reports, 486(3-5), 75-174. doi:10.1016/j.physrep.2009.11.002 ; Gelman, A., & King, G. (1993). Why Are American Presidential Election Campaign Polls So Variable When Votes Are So Predictable? British Journal of Political Science, 23(4), 409-451. doi:10.1017/s0007123400006682 ; Gonçalves, B., Perra, N., & Vespignani, A. (2011). Modeling Users’ Activity on Twitter Networks: Validation of Dunbar’s Number. PLoS ONE, 6(8), e22656. doi:10.1371/journal.pone.0022656 ; González, M. C., Hidalgo, C. A., & Barabási, A.-L. (2008). Understanding individual human mobility patterns. Nature, 453(7196), 779-782. doi:10.1038/nature06958 ; Hernández-Castañeda, Á., Calvo, H., & Gambino, O. J. (2018). Impact of polarity in deception detection. Journal of Intelligent & Fuzzy Systems, 35(1), 549-558. doi:10.3233/jifs-169610 ; Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabási, A.-L., Brewer, D., … Van Alstyne, M. (2009). Computational Social Science. Science, 323(5915), 721-723. doi:10.1126/science.1167742 ; Mohammad, S. M., Sobhani, P., & Kiritchenko, S. (2017). Stance and Sentiment in Tweets. ACM Transactions on Internet Technology, 17(3), 1-23. doi:10.1145/3003433 ; Mohammad, S. M., & Turney, P. D. (2012). CROWDSOURCING A WORD-EMOTION ASSOCIATION LEXICON. Computational Intelligence, 29(3), 436-465. doi:10.1111/j.1467-8640.2012.00460.x ; Pang, B., & Lee, L. (2008). Opinion Mining and Sentiment Analysis. Foundations and Trends® in Information Retrieval, 2(1–2), 1-135. doi:10.1561/1500000011 ; Pennebaker J.W. , Francis M.E. and Booth R.J. , Linguistic Inquiry and Word Count: LIWC 2001, Mahway: Lawrence Erlbaum Associates 71 (2001). ; Sulis, E., Irazú Hernández Farías, D., Rosso, P., Patti, V., & Ruffo, G. (2016). Figurative messages and affect in Twitter: Differences between #irony, #sarcasm and #not. Knowledge-Based Systems, 108, 132-143. doi:10.1016/j.knosys.2016.05.035 ; Theocharis, Y., & Lowe, W. (2015). Does Facebook increase political participation? Evidence from a field experiment. Information, Communication & Society, 19(10), 1465-1486. doi:10.1080/1369118x.2015.1119871 ; Whissell, C. (2009). Using the Revised Dictionary of Affect in Language to Quantify the Emotional Undertones of Samples of Natural Language. Psychological Reports, 105(2), 509-521. doi:10.2466/pr0.105.2.509-521 Keyword: Brexit; Community detection; LENGUAJES Y SISTEMAS INFORMATICOS; NLP; Stance detection; Twitter URL: https://doi.org/10.3233/JIFS-179895 http://hdl.handle.net/10251/170080 BASE Hide details 11 Multilingual Stance Detection in Social Media Political Debates Lai, Mirko; Cignarella, Alessandra Teresa; Hernandez-Farias, Delia Irazu. - : Elsevier, 2020 BASE Show details 12 Political Opinion Mining and Analysis for Social Media Kannangara, Sandeepa Harshanganie, Computer Science & Engineering, Faculty of Engineering, UNSW. - : University of New South Wales. Computer Science & Engineering, 2019 BASE Show details 13 Stance Detection and Analysis in Social Media Sobhani, Parinaz. - : Université d'Ottawa / University of Ottawa, 2017 BASE Show details

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