A percepção dos usuários sobre a utilização da análise de sentimentos como apoio à seleção de notícias
Pages 216 - 225
Abstract
Everyday, readers are bombarded with various types of news (positive or negative) without having the chance to choose what they want to read. In this paper we investigate the use of sentiment analysis to support the user in the content selection. We present Magnet News, a Web tool where readers can choose the polarity of the news they want to read. In this scenario we use the Underlying Discourse Unveiling Method (UDUM) to evaluate the user experience in relation to the proposal. Our results show that the sentiment analysis can be an important mechanism to support users in the news choice.
References
[1]
Sentistrength 2.0. http://sentistrength.wlv.ac.uk/Download.
[2]
Why do people read online news? http://onlinejournalismblog.com/2010/04/27/why-do-people-read-online-news-research-summary/.
[3]
Antoniades, D., Polakis, I., Kontaxis, G., Athanasopoulos, E., Ioannidis, S., Markatos, E. P., and Karagiannis, T. We.b: The web of short urls. In 20th International Conference on World Wide Web, ACM (2011), 715--724.
[4]
Araújo, M., Gonçalves, P., Benevenuto, F., and Cha, M. ifeel: A system that compares and combines sentiment analysis methods. In WWW (Companion Volume), International World Wide Web Conference (WWW'14) (2014).
[5]
Biswas, R., Riffe, D., and Zillmann, D. Mood influence on the appeal of bad news. Journalism & Mass Communication Quarterly 71, 3 (1994), 689--696.
[6]
da Silva, E. J., de Souza, C. S., Prates, R. O., and Nicolaci-da Costa, A. M. What they want and what they get: A study of light-weight technologies for online communities. In Proceedings of the Latin American conference on Human-computer interaction, ACM (2003), 135--146.
[7]
De Souza, C. S., Nicolaci-da Costa, A. M., da Silva, E. J., and Prates, R. O. Compulsory institutionalization: investigating the paradox of computer-supported informal social processes. Interacting with Computers 16, 4 (2004), 635--656.
[8]
Gomide, J., Veloso, A., Jr., W. M., Almeida, V., Benevenuto, F., Ferraz, F., and Teixeira, M. Dengue surveillance based on a computational model of spatio-temporal locality of twitter. In ACM Web Science Conference (WebSci) (2011).
[9]
Gonçalves, P., Araújo, M., Benevenuto, F., and Cha, M. Comparing and combining sentiment analysis methods. In Proceedings of the 1st ACM Conference on Online Social Networks (COSN'13) (2013).
[10]
Goncalves, P., Benevenuto, F., and Almeida, V. O que tweets contendo emoticons podem revelar sobre sentimentos coletivos. In II Brazilian Workshop on Social Network Analysis and Mining (BraSNAM) (2013).
[11]
Goncalves, P., Dores, W., and Benevenuto, F. Panas-t: Uma escala psicometrica para analise de sentimentos no twitter. In I Brazilian Workshop on Social Network Analysis and Mining (BraSNAM) (2012).
[12]
Hannak, A., Anderson, E., Barrett, L. F., Lehmann, S., Mislove, A., and Riedewald, M. Tweetin'in the rain: Exploring societal-scale effects of weather on mood. In ICWSM (2012).
[13]
Lamb, A., Paul, M. J., and Dredze, M. Separating fact from fear: Tracking flu infections on twitter. In Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (June 2013), 789--795.
[14]
Liu, B. Sentiment analysis and opinion mining. Synthesis Lectures on Human Language Technologies 5, 1 (2012), 1--167.
[15]
Narayanan, R., Liu, B., and Choudhary, A. Sentiment analysis of conditional sentences. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1-Volume 1, Association for Computational Linguistics (2009), 180--189.
[16]
Nguyen, A., Legg, A., and Sweeny, K. Do you want the good news or the bad news first? news order influences recipients' mood, perceptions, and behaviors. In UCR Undergraduate Research Journal (2011).
[17]
Nguyen, A., Legg, A., and Sweeny, K. Do you want the good news or the bad news first? news order influences recipients' mood, perceptions, and behaviors. UCR Undergraduate Research Journal 5 (2011), 31--36.
[18]
Nicolaci-da Costa, A. Análise de discurso e pesquisa qualitativa. Anais da 18a. Reunião Anual da Sociedade de Psicologia de Ribeirão Preto (1989).
[19]
Nicolaci-da Costa, A. M., Leitão, C. F., and Romão-Dias, D. Como conhecer usuários através do método de explicitação do discurso subjacente (meds). VI Simpósio Brasileiro sobre Fatores Humanos em Sistemas Computacionais, IHC (2004), 47--56.
[20]
O'Connor, B., Balasubramanyan, R., Routledge, B. R., and Smith, N. A. From tweets to polls: Linking text sentiment to public opinion time series. ICWSM 11 (2010), 122--129.
[21]
Pang, B., Lee, L., and Vaithyanathan, S. Thumbs up?: sentiment classification using machine learning techniques. In Proceedings of the ACL-02 conference on Empirical methods in natural language processing-Volume 10, Association for Computational Linguistics (2002), 79--86.
[22]
Sakaki, T., Okazaki, M., and Matsuo, Y. Earthquake shakes twitter users: real-time event detection by social sensors. In Int'l Conference on World wide web (WWW) (2010), 851--860.
[23]
Thelwall, M. Heart and soul: Sentiment strength detection in the social web with sentistrength. http://migre.me/fHgj9.
[24]
Tumasjan, A., Sprenger, T. O., Sandner, P. G., and Welpe, I. M. Predicting elections with twitter: What 140 characters reveal about political sentiment. In Int'l AAAI Conference on Weblogs and Social Media (ICWSM) (2010).
[25]
Zillmann, D., and Bryant, J. Affect, mood, and emotion as determinants of selective exposure. Selective exposure to communication (1985), 157--190.
Index Terms
- A percepção dos usuários sobre a utilização da análise de sentimentos como apoio à seleção de notícias
Comments
Information & Contributors
Information
Published In
October 2014
492 pages
ISBN:9788576692911
- General Chairs:
- Clodis Boscarioli,
- Sílvia Amélia Bim,
- Program Chairs:
- Carla Leitão,
- Cristiano Maciel
Sponsors
- Springer
- SBC: Brazilian Computer Society
- CAIXA: CAIXA
- PTI: Parque Tecnológico Itaipu
- NICBR: Nucleo de Informatcao e Coordenacao do Ponto BR
- CNPq: Conselho Nacional de Desenvolvimento Cientifico e Tecn
- Intel: Intel
- Fundação Araucária: Fundação Araucária de Apoio ao Desenvolvimento Científico e Tecnológico do Paraná
- Fundação para a Ciência e Tecnologia, Ministério da Ciência e Ensino Superior: Fundação para a Ciência e Tecnologia, Ministério da Ciência e Ensino Superior
- CGIBR: Comite Gestor da Internet no Brazil
- IDF: The Interaction Design Foundation
- CAPES: Brazilian Higher Education Funding Council
Publisher
Sociedade Brasileira de Computação
Brazil
Publication History
Published: 27 October 2014
Author Tags
Qualifiers
- Research-article
Acceptance Rates
Overall Acceptance Rate 331 of 973 submissions, 34%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 60Total Downloads
- Downloads (Last 12 months)25
- Downloads (Last 6 weeks)8
Reflects downloads up to 11 Jan 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in