Assembly of polarity, emotion and user statistics for detection of fake profiles Notebook for PAN at CLEF 2020
The explosive growth of fake news on social networks has aroused great interest from researchers in different disciplines. To achieve efficient and effective detection of fake news requires scientific contributions from various disciplines, such as computational linguistics, artificial intelligence,...
- Autores:
-
Moreno-Sandoval, Luis Gabriel
Puertas, Edwin
Pomares-Quimbaya, Alexandra
Alvarado-Valencia, Jorge Andres
- Tipo de recurso:
- Fecha de publicación:
- 2020
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/12286
- Acceso en línea:
- https://scopus.utb.elogim.com/record/display.uri?eid=2-s2.0-85121794424&origin=resultslist&sort=plf-f&src=s&sid=5b5924365d87681725a9d6c17daad1d5&sot=b&sdt=b&s=TITLE-ABS-KEY%28Assembly+of+polarity%2C+emotion+and+user+statistics+for+detection+of+fake+profiles+Notebook+for+PAN+at+CLEF+2020%29&sl=125&sessionSearchId=5b5924365d87681725a9d6c17daad1d5
https://hdl.handle.net/20.500.12585/12286
- Palabra clave:
- Rumor;
Social Media;
Disinformation
LEMB
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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Assembly of polarity, emotion and user statistics for detection of fake profiles Notebook for PAN at CLEF 2020 |
| title |
Assembly of polarity, emotion and user statistics for detection of fake profiles Notebook for PAN at CLEF 2020 |
| spellingShingle |
Assembly of polarity, emotion and user statistics for detection of fake profiles Notebook for PAN at CLEF 2020 Rumor; Social Media; Disinformation LEMB |
| title_short |
Assembly of polarity, emotion and user statistics for detection of fake profiles Notebook for PAN at CLEF 2020 |
| title_full |
Assembly of polarity, emotion and user statistics for detection of fake profiles Notebook for PAN at CLEF 2020 |
| title_fullStr |
Assembly of polarity, emotion and user statistics for detection of fake profiles Notebook for PAN at CLEF 2020 |
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Assembly of polarity, emotion and user statistics for detection of fake profiles Notebook for PAN at CLEF 2020 |
| title_sort |
Assembly of polarity, emotion and user statistics for detection of fake profiles Notebook for PAN at CLEF 2020 |
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Moreno-Sandoval, Luis Gabriel Puertas, Edwin Pomares-Quimbaya, Alexandra Alvarado-Valencia, Jorge Andres |
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Moreno-Sandoval, Luis Gabriel Puertas, Edwin Pomares-Quimbaya, Alexandra Alvarado-Valencia, Jorge Andres |
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Rumor; Social Media; Disinformation |
| topic |
Rumor; Social Media; Disinformation LEMB |
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LEMB |
| description |
The explosive growth of fake news on social networks has aroused great interest from researchers in different disciplines. To achieve efficient and effective detection of fake news requires scientific contributions from various disciplines, such as computational linguistics, artificial intelligence, and sociology. Here we illustrate how polarity, emotion, and user statistics can be used to detect fake profiles on Twitter’s social network. This paper presents a novel strategy for the characterization of the Twitter profile based on the generation of an assembly of polarity, emotion, and user statistics characteristics that serve as input to a set of classifiers. The results are part of our participation in the PAN 2020 in the CLEF in the task of Profiling Fake News Spreaders on Twitter. Copyright © 2020 for this paper by its authors. |
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2020 |
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2020 |
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2023-07-21T15:47:38Z |
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2023-07-21T15:47:38Z |
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2023 |
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Moreno-Sandoval, L. G., Puertas, E., Pomares-Quimbaya, A., & Alvarado-Valencia, J. A. (s/f). Notebook for PAN at CLEF 2020. Webis.de. Recuperado el 14 de julio de 2023, de https://pan.webis.de/downloads/publications/papers/morenosandoval_2020.pdf |
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Universidad Tecnológica de Bolívar |
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Repositorio Universidad Tecnológica de Bolívar |
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Moreno-Sandoval, L. G., Puertas, E., Pomares-Quimbaya, A., & Alvarado-Valencia, J. A. (s/f). Notebook for PAN at CLEF 2020. Webis.de. Recuperado el 14 de julio de 2023, de https://pan.webis.de/downloads/publications/papers/morenosandoval_2020.pdf Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
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Moreno-Sandoval, Luis Gabrielebd4011f-e093-46cc-97aa-9e841c4c41e2Puertas, Edwin5a1b1566-e112-43dc-8ac7-310ea9af8f05Pomares-Quimbaya, Alexandraf50a0d31-dc2f-4e05-aa15-e82c9c3c60f0Alvarado-Valencia, Jorge Andres902a19a4-4028-4417-95b1-293c7f1169cb2023-07-21T15:47:38Z2023-07-21T15:47:38Z20202023Moreno-Sandoval, L. G., Puertas, E., Pomares-Quimbaya, A., & Alvarado-Valencia, J. A. (s/f). Notebook for PAN at CLEF 2020. Webis.de. Recuperado el 14 de julio de 2023, de https://pan.webis.de/downloads/publications/papers/morenosandoval_2020.pdfhttps://scopus.utb.elogim.com/record/display.uri?eid=2-s2.0-85121794424&origin=resultslist&sort=plf-f&src=s&sid=5b5924365d87681725a9d6c17daad1d5&sot=b&sdt=b&s=TITLE-ABS-KEY%28Assembly+of+polarity%2C+emotion+and+user+statistics+for+detection+of+fake+profiles+Notebook+for+PAN+at+CLEF+2020%29&sl=125&sessionSearchId=5b5924365d87681725a9d6c17daad1d5https://hdl.handle.net/20.500.12585/12286Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThe explosive growth of fake news on social networks has aroused great interest from researchers in different disciplines. To achieve efficient and effective detection of fake news requires scientific contributions from various disciplines, such as computational linguistics, artificial intelligence, and sociology. Here we illustrate how polarity, emotion, and user statistics can be used to detect fake profiles on Twitter’s social network. This paper presents a novel strategy for the characterization of the Twitter profile based on the generation of an assembly of polarity, emotion, and user statistics characteristics that serve as input to a set of classifiers. The results are part of our participation in the PAN 2020 in the CLEF in the task of Profiling Fake News Spreaders on Twitter. Copyright © 2020 for this paper by its authors.8 páginasapplication/pdfenghttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf2CEUR Workshop ProceedingsAssembly of polarity, emotion and user statistics for detection of fake profiles Notebook for PAN at CLEF 2020info:eu-repo/semantics/articleinfo:eu-repo/semantics/drafthttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/version/c_b1a7d7d4d402bccehttp://purl.org/coar/resource_type/c_2df8fbb1Rumor;Social Media;DisinformationLEMBCartagena de IndiasAhmed, H., Traore, I., Saad, S. Detection of Online Fake News Using N-Gram Analysis and Machine Learning Techniques (2017) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10618 LNCS, pp. 127-138. Cited 297 times. http://springerlink.com/content/0302-9743/copyright/2005/ ISBN: 978-331969154-1 doi: 10.1007/978-3-319-69155-8_9Ahmed, H., Traore, I., Saad, S. Detecting opinion spams and fake news using text classification (2018) Security and Privacy, 1 (1), p. e9. Cited 205 times.Bondielli, A., Marcelloni, F. A survey on fake news and rumour detection techniques (2019) Information Sciences, 497, pp. 38-55. Cited 281 times. http://www.journals.elsevier.com/information-sciences/ doi: 10.1016/j.ins.2019.05.035Cui, L., Wang, S., Lee, D. Same: Sentiment-aware multi-modal embedding for detecting fake news (2019) Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019, pp. 41-48. Cited 63 times. http://dl.acm.org/citation.cfm?id=3341161 ISBN: 978-145036868-1 doi: 10.1145/3341161.3342894Ghanem, B., Rosso, P., Rangel, F. An Emotional Analysis of False Information in Social Media and News Articles (2020) ACM Transactions on Internet Technology, 20 (2), art. no. 3381750. Cited 111 times. http://dl.acm.org/citation.cfm?id=J780 doi: 10.1145/3381750Giachanou, A., Ríssola, E.A., Ghanem, B., Crestani, F., Rosso, P. The role of personality and linguistic patterns in discriminating between fake news spreaders and fact checkers (2020) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12089 LNCS, pp. 181-192. Cited 37 times. https://www.springer.com/series/558 ISBN: 978-303051309-2 doi: 10.1007/978-3-030-51310-8_17Imran, M., Castillo, C., Diaz, F., Vieweg, S. Processing Social Media Messages in Mass Emergency: Survey Summary (2018) The Web Conference 2018 - Companion of the World Wide Web Conference, WWW 2018, pp. 507-511. Cited 65 times. http://dl.acm.org/citation.cfm?id=3184558 ISBN: 978-145035640-4 doi: 10.1145/3184558.3186242Jwa, H., Oh, D., Park, K., Kang, J.M., Lim, H. exBAKE: Automatic fake news detection model based on Bidirectional Encoder Representations from Transformers (BERT) (2019) Applied Sciences (Switzerland), 9 (19), art. no. 4062. Cited 111 times. https://res.mdpi.com/d_attachment/applsci/applsci-09-04062/article_deploy/applsci-09-04062-v4.pdf doi: 10.3390/app9194062Kochkina, E., Liakata, M., Augenstein, I. (2017) Turing at semeval-2017 task 8: Sequential approach to rumour stance classification with branch-lstm. Cited 39 times. arXiv preprint arXiv:1704.07221Lazer, D.M.J., Baum, M.A., Benkler, Y., Berinsky, A.J., Greenhill, K.M., Menczer, F., Metzger, M.J., (...), Zittrain, J.L. The science of fake news: Addressing fake news requires a multidisciplinary effort (2018) Science, 359 (6380), pp. 1094-1096. Cited 1877 times. http://science.sciencemag.org/content/359/6380/1094/tab-pdf doi: 10.1126/science.aao2998Long, Y. Fake news detection through multi-perspective speaker profiles (2017) Association for Computational Linguistics. Cited 8 times.Mohammad, S.M., Turney, P.D. Crowdsourcing a word-emotion association lexicon (Open Access) (2013) Computational Intelligence, 29 (3), pp. 436-465. Cited 1418 times. doi: 10.1111/j.1467-8640.2012.00460.xMoreno-Sandoval, L.G., Beltrán-Herrera, P., Vargas-Cruz, J.A., Sánchez-Barriga, C., Pomares-Quimbaya, A., Alvarado-Valencia, J.A., García-Díaz, J.C. CSL: A Combined Spanish lexicon: Resource for polarity classification and sentiment analysis (Open Access) (2017) ICEIS 2017 - Proceedings of the 19th International Conference on Enterprise Information Systems, 1, pp. 288-295. Cited 10 times. http://www.scitepress.org/DigitalLibrary/HomePage.aspx ISBN: 978-989758247-9 doi: 10.5220/0006336402880295Potthast, M., Gollub, T., Wiegmann, M., Stein, B. 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