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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 Page: 1 2 3 Hits 1 – 20 of 59 1 Emotionally Informed Hate Speech Detection: A Multi-target Perspective Chiril, Patricia; Pamungkas, Endang Wahyu; Benamara, Farah... In: ISSN: 1866-9956 ; EISSN: 1866-9964 ; Cognitive Computation ; https://hal.archives-ouvertes.fr/hal-03275549 ; Cognitive Computation, Springer, 2021, 13 (4), &#x27E8;10.1007/s12559-021-09862-5&#x27E9; ; https://link.springer.com/article/10.1007%2Fs12559-021-09862-5 (2021) BASE Show details 2 Emotionally Informed Hate Speech Detection: A Multi-target Perspective Chiril, Patricia; Pamungkas, Endang Wahyu; Benamara, Farah... In: Cognit Comput (2021) BASE Show details 3 Sentiment Analysis of Latin Poetry: First Experiments on the Odes of Horace Sprugnoli, Rachele (orcid:0000-0001-6861-5595); Mambrini, Francesco (orcid:0000-0003-0834-7562); Passarotti, Marco (orcid:0000-0002-9806-7187). - : CEUR Workshop Proceedings (CEUR-WS.org), 2021. : country:ITA, 2021. : place:MILANO -- ITA, 2021 BASE Show details 4 Linking the Lewis & Short Dictionary to the LiLa Knowledge Base of Interoperable Linguistic Resources for Latin Mambrini, Francesco (orcid:0000-0003-0834-7562); Litta, Eleonora (orcid:0000-0002-0499-997X); Passarotti, Marco (orcid:0000-0002-9806-7187). - : CEUR Workshop Proceedings (CEUR-WS.org), 2021. : country:ITA, 2021. : place:MILANO -- ITA, 2021 BASE Show details 5 Preface Fersini, Elisabetta; Patti, Viviana; Passarotti, Marco (orcid:0000-0002-9806-7187). - : CEUR Workshop Proceedings (CEUR-WS.org), 2021. : country:ITA, 2021. : place:MILANO -- ITA, 2021 BASE Show details 6 Proceedings of the Eighth Italian Conference on Computational Linguistics (CLiC-it 2021). Milan, Italy, January 26-28, 2022 Patti, Viviana; Passarotti, Marco (orcid:0000-0002-9806-7187); Fersini, Elisabetta. - : CEUR Workshop Proceedings (CEUR-WS.org), 2021. : country:ITA, 2021. : place:MILANO -- ITA, 2021 BASE Show details 7 The Annotation of Liber Abbaci, a Domain-Specific Latin Resource Cecchini, Flavio Massimiliano; Francesco, Grotto; Maria, Simi. - : CEUR Workshop Proceedings (CEUR-WS.org), 2021. : country:ITA, 2021. : place:MILANO -- ITA, 2021 BASE Show details 8 Categorizing Misogynistic Behaviours in Italian, English and Spanish Tweets ; Categorización de comportamientos misóginos en tweets en italiano, inglés y español Lazzardi, Silvia; Patti, Viviana; Rosso, Paolo. - : Sociedad Española para el Procesamiento del Lenguaje Natural, 2021 BASE Show details 9 Emotionally Informed Hate Speech Detection: A Multi-target Perspective Chiril, Patricia; Pamungkas, Endang Wahyu; Benamara, Farah. - 2021 BASE Show details 10 Resources and benchmark corpora for hate speech detection: a systematic review [<Journal>] Poletto, Fabio [Verfasser]; Basile, Valerio [Verfasser]; Sanguinetti, Manuela [Verfasser]. DNB Subject Category Language Show details 11 Personal-ITY: A Novel YouTube-based Corpus for Personality Prediction in Italian ... Bassignana, Elisa; Nissim, Malvina; Patti, Viviana. - : arXiv, 2020 BASE Show details 12 Matching Theory and Data with Personal-ITY: What a Corpus of Italian YouTube Comments Reveals About Personality ... The 28th International Conference on Computational Linguistics 2020; Bassignana, Elisa; Nissim, Malvina. - : Underline Science Inc., 2020 BASE Show details 13 Modeling Annotator Perspective and Polarized Opinions to Improve Hate Speech Detection Akhtar, Sohail; Basile, Valerio; Patti, Viviana In: Proceedings of the AAAI Conference on Human Computation and Crowdsourcing; Vol 8 No 1 (2020): Proceedings of the Eighth AAAI Conference on Human Computation and Crowdsourcing; 151-154 (2020) BASE Show details 14 Modeling Annotator Perspective and Polarized Opinions to Improve Hate Speech Detection Akhtar, Sohail; Basile, Valerio; Patti, Viviana In: Proceedings of the AAAI Conference on Human Computation and Crowdsourcing; Vol. 8 No. 1 (2020): Proceedings of the Eighth AAAI Conference on Human Computation and Crowdsourcing; 151-154 (2020) BASE Show details 15 HurtBERT: Incorporating Lexical Features with BERT for the Detection of Abusive Language Koufakou, Anna; Pamungkas, Endang Wahyu; Basile, Valerio. - : Association for Computational Linguistics, 2020. : country:USA, 2020. : place:209 N EIGHTH STREET, STROUDSBURG, PA 18360 USA, 2020 BASE Show details 16 EVALITA4ELG: Italian Benchmark Linguistic Resources, NLP Services and Tools for the ELG Platform Patti, Viviana; Basile, Valerio; Bosco, Cristina. - 2020 BASE Show details 17 Do Linguistic Features Help Deep Learning? The Case of Aggressiveness in Mexican Tweets Frenda, Simona; Banerjee, Somnath; Rosso, Paolo. - 2020 BASE Show details 18 “Contro L’Odio”: A Platform for Detecting, Monitoring and Visualizing Hate Speech against Immigrants in Italian Social Media Capozzi, Arthur; Lai, Mirko; Basile, Valerio. - 2020 BASE Show details 19 Do Linguistic Features Help Deep Learning? The Case of Aggressiveness in Mexican Tweets Frenda, Simona; Banerjee, Somnath; Rosso, Paolo. - : Instituto Politecnico Nacional/Centro de Investigacion en Computacion, 2020 BASE Show details 20 #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 Page: 1 2 3

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