Journal articles on the topic 'Corpus de tweets'
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Mitra, Tanushree, and Eric Gilbert. "CREDBANK: A Large-Scale Social Media Corpus With Associated Credibility Annotations." Proceedings of the International AAAI Conference on Web and Social Media 9, no. 1 (August 3, 2021): 258–67. http://dx.doi.org/10.1609/icwsm.v9i1.14625.
Chen, Lu, Wenbo Wang, Meenakshi Nagarajan, Shaojun Wang, and Amit Sheth. "Extracting Diverse Sentiment Expressions with Target-Dependent Polarity from Twitter." Proceedings of the International AAAI Conference on Web and Social Media 6, no. 1 (August 3, 2021): 50–57. http://dx.doi.org/10.1609/icwsm.v6i1.14252.
Yang, Yuan-Chi, Mohammed Ali Al-Garadi, Whitney Bremer, Jane M. Zhu, David Grande, and Abeed Sarker. "Developing an Automatic System for Classifying Chatter About Health Services on Twitter: Case Study for Medicaid." Journal of Medical Internet Research 23, no. 5 (May 3, 2021): e26616. http://dx.doi.org/10.2196/26616.
Al-Twairesh, Nora, Hend Al-Khalifa, AbdulMalik Al-Salman, and Yousef Al-Ohali. "AraSenTi-Tweet: A Corpus for Arabic Sentiment Analysis of Saudi Tweets." Procedia Computer Science 117 (2017): 63–72. http://dx.doi.org/10.1016/j.procs.2017.10.094.
Abayomi-Alli, Adebayo, Olusola Abayomi-Alli, Sanjay Misra, and Luis Fernandez-Sanz. "Study of the Yahoo-Yahoo Hash-Tag Tweets Using Sentiment Analysis and Opinion Mining Algorithms." Information 13, no. 3 (March 15, 2022): 152. http://dx.doi.org/10.3390/info13030152.
V, Ashwin. "Twitter Tweet Classifier." IAES International Journal of Artificial Intelligence (IJ-AI) 5, no. 1 (March 1, 2016): 41. http://dx.doi.org/10.11591/ijai.v5.i1.pp41-44.
Park, Jung Ran, and Houda El Mimouni. "Emoticons and non-verbal communications across Arabic, English, and Korean Tweets." Global Knowledge, Memory and Communication 69, no. 8/9 (June 6, 2020): 579–95. http://dx.doi.org/10.1108/gkmc-02-2020-0021.
Li, Quanzhi, Sameena Shah, Xiaomo Liu, and Armineh Nourbakhsh. "Data Sets: Word Embeddings Learned from Tweets and General Data." Proceedings of the International AAAI Conference on Web and Social Media 11, no. 1 (May 3, 2017): 428–36. http://dx.doi.org/10.1609/icwsm.v11i1.14859.
Vieira da Silva, Fernando J., Norton T. Roman, and Ariadne M. B. R. Carvalho. "Stock market tweets annotated with emotions." Corpora 15, no. 3 (November 2020): 343–54. http://dx.doi.org/10.3366/cor.2020.0203.
McDonald, Graham, Romain Deveaud, Richard McCreadie, Craig Macdonald, and Iadh Ounis. "Tweet Enrichment for Effective Dimensions Classification in Online Reputation Management." Proceedings of the International AAAI Conference on Web and Social Media 9, no. 1 (August 3, 2021): 654–57. http://dx.doi.org/10.1609/icwsm.v9i1.14674.
Smułczyński, Michał. "Microblogging in Denmark and Poland — a contrastive analysis. Part II." Scandinavian Philology 19, no. 2 (2021): 285–312. http://dx.doi.org/10.21638/11701/spbu21.2021.205.
Slemp, Katie. "Attitudes towards varied inclusive language use in Spanish on Twitter." Working papers in Applied Linguistics and Linguistics at York 1 (September 13, 2021): 60–74. http://dx.doi.org/10.25071/2564-2855.6.
Maceda, Lany L., Jennifer L. Llovido, and Thelma D. Palaoag. "Corpus Analysis of Earthquake Related Tweets through Topic Modelling." International Journal of Machine Learning and Computing 7, no. 6 (December 2017): 194–97. http://dx.doi.org/10.18178/ijmlc.2017.7.6.645.
Roberts, Helen, Bernd Resch, Jon Sadler, Lee Chapman, Andreas Petutschnig, and Stefan Zimmer. "Investigating the Emotional Responses of Individuals to Urban Green Space Using Twitter Data: A Critical Comparison of Three Different Methods of Sentiment Analysis." Urban Planning 3, no. 1 (March 29, 2018): 21–33. http://dx.doi.org/10.17645/up.v3i1.1231.
Shin, Han-Sub, Hyuk-Yoon Kwon, and Seung-Jin Ryu. "A New Text Classification Model Based on Contrastive Word Embedding for Detecting Cybersecurity Intelligence in Twitter." Electronics 9, no. 9 (September 18, 2020): 1527. http://dx.doi.org/10.3390/electronics9091527.
Dynel, Marta. "#HaStatoPutin Affinity Space: From Political Work to Autotelic Humor." Social Media + Society 8, no. 4 (October 2022): 205630512211387. http://dx.doi.org/10.1177/20563051221138760.
Alruily, Meshrif. "Issues of Dialectal Saudi Twitter Corpus." International Arab Journal of Information Technology 17, no. 3 (May 1, 2019): 367–74. http://dx.doi.org/10.34028/iajit/17/3/10.
Fernández-Martínez, Nicolás José. "The FGLOCTweet Corpus: An English tweet-based corpus for fine-grained location-detection tasks." Research in Corpus Linguistics 10, no. 1 (2022): 117–33. http://dx.doi.org/10.32714/ricl.10.01.06.
Breeze, Ruth. "Angry tweets." Journal of Language Aggression and Conflict 8, no. 1 (February 25, 2020): 118–45. http://dx.doi.org/10.1075/jlac.00033.bre.
Baig, Amber, Mutee U. Rahman, Hameedullah Kazi, and Ahsanullah Baloch. "Developing a POS Tagged Corpus of Urdu Tweets." Computers 9, no. 4 (November 7, 2020): 90. http://dx.doi.org/10.3390/computers9040090.
Singh, Purva. "Covhindia: Deep Learning Framework for Sentiment Polarity Detection of Covid-19 Tweets in Hindi." International Journal on Natural Language Computing 9, no. 5 (October 30, 2020): 23–34. http://dx.doi.org/10.5121/ijnlc.2020.9502.
Pereira, Márcia Helena de Melo, and Ana Claudia Oliveira Azevedo. "A reelaboração de gêneros em tweets: propósitos comunicativos em 280 caracteres." Fórum Linguístico 19, no. 3 (November 23, 2022): 8232–51. http://dx.doi.org/10.5007/1984-8412.2022.e76925.
Tak, Raghu. "A Quantifiable Analysis of Ambivalence in Tweets." International Journal for Research in Applied Science and Engineering Technology 10, no. 4 (April 30, 2022): 691–99. http://dx.doi.org/10.22214/ijraset.2022.41340.
Weissenbacher, Davy, Abeed Sarker, Ari Klein, Karen O’Connor, Arjun Magge, and Graciela Gonzalez-Hernandez. "Deep neural networks ensemble for detecting medication mentions in tweets." Journal of the American Medical Informatics Association 26, no. 12 (September 27, 2019): 1618–26. http://dx.doi.org/10.1093/jamia/ocz156.
Escamilla, Imelda, Clodoveu A. Davis Jr., Marco Moreno-Ibarra, and Vladimir Luna. "Geocoding of Spatial Relationships Contained in Tweets." International Journal of Knowledge Society Research 7, no. 1 (January 2016): 26–42. http://dx.doi.org/10.4018/ijksr.2016010102.
Tahir, Bilal, and Muhammad Amir Mehmood. "Anbar: Collection and analysis of a large scale Urdu language Twitter corpus." Journal of Intelligent & Fuzzy Systems 42, no. 5 (March 31, 2022): 4789–800. http://dx.doi.org/10.3233/jifs-219266.
Almuqren, Latifah, and Alexandra Cristea. "AraCust: a Saudi Telecom Tweets corpus for sentiment analysis." PeerJ Computer Science 7 (May 20, 2021): e510. http://dx.doi.org/10.7717/peerj-cs.510.
Valdez, Danny, and Jennifer B. Unger. "Difficulty Regulating Social Media Content of Age-Restricted Products: Comparing JUUL’s Official Twitter Timeline and Social Media Content About JUUL." JMIR Infodemiology 1, no. 1 (December 7, 2021): e29011. http://dx.doi.org/10.2196/29011.
Makowska, Magdalena. "#naukanatwitterze. O multimodalnym designie informacji w dyskursie cyfrowym." Forum Lingwistyczne, no. 7 (November 20, 2020): 89–104. http://dx.doi.org/10.31261/fl.2020.07.07.
Schaefer, Robin, and Manfred Stede. "Argument Mining on Twitter: A survey." it - Information Technology 63, no. 1 (February 1, 2021): 45–58. http://dx.doi.org/10.1515/itit-2020-0053.
Martínez-Cámara, Eugenio, M. Teresa Martín-Valdivia, L. Alfonso Ureña-López, and Ruslan Mitkov. "Polarity classification for Spanish tweets using the COST corpus." Journal of Information Science 41, no. 3 (February 3, 2015): 263–72. http://dx.doi.org/10.1177/0165551514566564.
Sulaiman, Hamdun, Muhamad Ryansyah, Kudiantoro Widianto, Sidik Sidik, and Andria Nugraha. "Implementasi Machine Learning Dengan Metode Text Mining Pada Twitter." Infotek : Jurnal Informatika dan Teknologi 7, no. 1 (January 20, 2024): 52–62. http://dx.doi.org/10.29408/jit.v7i1.23734.
Bel-Enguix, Gemma, Helena Gómez-Adorno, Alejandro Pimentel, Sergio-Luis Ojeda-Trueba, and Brian Aguilar-Vizuet. "Negation Detection on Mexican Spanish Tweets: The T-MexNeg Corpus." Applied Sciences 11, no. 9 (April 25, 2021): 3880. http://dx.doi.org/10.3390/app11093880.
Al-Laith, Ali, Muhammad Shahbaz, Hind F. Alaskar, and Asim Rehmat. "AraSenCorpus: A Semi-Supervised Approach for Sentiment Annotation of a Large Arabic Text Corpus." Applied Sciences 11, no. 5 (March 9, 2021): 2434. http://dx.doi.org/10.3390/app11052434.
Albu, Elena. "“Tired, emotional and very very happy. Fantastic day #AFC.” The Expression of Emotions on Twitter during the 2014 European Elections." Recherches anglaises et nord-américaines 51, no. 1 (2018): 57–70. http://dx.doi.org/10.3406/ranam.2018.1564.
Kuhaneswaran, Banujan, Banage T. G. S. Kumara, and Incheon Paik. "Strengthening Post-Disaster Management Activities by Rating Social Media Corpus." International Journal of Systems and Service-Oriented Engineering 10, no. 1 (January 2020): 34–50. http://dx.doi.org/10.4018/ijssoe.2020010103.
Schneider, Ulrike. "How Trump tweets: A comparative analysis of tweets by US politicians." Research in Corpus Linguistics 9, no. 2 (2021): 34–63. http://dx.doi.org/10.32714/ricl.09.02.03.
Xu, Xiaoyu, Jeroen Gevers, and Luca Rossi. "“Can I write this is ableist AF in a peer review?”: A corpus-driven analysis of Twitter engagement strategies across disciplinary groups." Ibérica, no. 46 (December 15, 2023): 207–36. http://dx.doi.org/10.17398/2340-2784.46.207.
Papaccio, Mara. "Matteo Salvini auf Twitter: eine Analyse ausgewählter sprachlicher, stilistischer und rhetorischer Strategien." Italienisch 44, no. 87 (September 5, 2022): 64–80. http://dx.doi.org/10.24053/ital-2022-0007.
Camargo, Jorge E., Vladimir Vargas-Calderon, Nelson Vargas, and Liliana Calderón-Benavides. "Sentiment polarity classification of tweets using a extended dictionary." Inteligencia Artificial 21, no. 62 (September 7, 2018): 1. http://dx.doi.org/10.4114/intartif.vol21iss62pp1-12.
Brogueira, Gaspar, Fernando Batista, and Joao P. Carvalho. "A Smart System for Twitter Corpus Collection, Management and Visualization." International Journal of Technology and Human Interaction 13, no. 3 (July 2017): 13–32. http://dx.doi.org/10.4018/ijthi.2017070102.
Baihaqi, Wiga Maulana, Muliasari Pinilih, and Miftakhul Rohmah. "Kombinasi K-Means dan Support Vector Machine (SVM) untuk Memprediksi Unsur Sara pada Tweet." Jurnal Teknologi Informasi dan Ilmu Komputer 7, no. 3 (May 22, 2020): 501. http://dx.doi.org/10.25126/jtiik.2020732126.
Knight, Dawn, Svenja Adolphs, and Ronald Carter. "CANELC: constructing an e-language corpus." Corpora 9, no. 1 (May 2014): 29–56. http://dx.doi.org/10.3366/cor.2014.0050.
Albanyan, Abdullah, and Eduardo Blanco. "Pinpointing Fine-Grained Relationships between Hateful Tweets and Replies." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 10 (June 28, 2022): 10418–26. http://dx.doi.org/10.1609/aaai.v36i10.21284.
Asraoui, Fadi Oukili. "Using the Machine Learning Naive Bayes Algorithms for Sentiment Analysis on Online Product Reviews in the Air of Energy Optimization." E3S Web of Conferences 412 (2023): 01071. http://dx.doi.org/10.1051/e3sconf/202341201071.
Alvi, Arooj. "A Corpus Analysis of Online Education Tweets During Covid-19." Pakistan Social Sciences Review 5, no. III (September 30, 2021): 376–91. http://dx.doi.org/10.35484/pssr.2021(5-iii)28.
Tarrade, Louis, Jean-Philippe Magué, and Jean-Pierre Chevrot. "Detecting and categorising lexical innovations in a corpus of tweets." Psychology of Language and Communication 26, no. 1 (January 1, 2022): 313–29. http://dx.doi.org/10.2478/plc-2022-15.
Pascual, Daniel, Pilar Mur-Dueñas, and Rosa Lorés. "Looking into international research groups’ digital discursive practices: Criteria and methodological steps taken towards the compilation of the EUROPRO digital corpus." Research in Corpus Linguistics 8, no. 2 (2020): 87–102. http://dx.doi.org/10.32714/ricl.08.02.05.
Canhasi, Ercan, and Rexhep Shijaku. "Using Twitter to collect a multi-dialectal corpus of Albanian using advanced geotagging and dialect modeling." PLOS ONE 18, no. 11 (November 27, 2023): e0294284. http://dx.doi.org/10.1371/journal.pone.0294284.
Haque, Md Enamul, Eddie C. Ling, Aminul Islam, and Mehmet Engin Tozal. "Predicting Domain Specific Personal Attitudes and Sentiment." International Journal of Semantic Computing 14, no. 02 (June 2020): 199–222. http://dx.doi.org/10.1142/s1793351x20400073.