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English Information

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Authors
# Name
1 Jonathas Harb(jonathasgabriel05@gmail.com,)
2 Karin Becker(karin.becker@inf.ufrgs.br)

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Reference
# Reference
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2 Anderson, B. (2005). Imagined communities. Chap, 4(Hansen 1999):48–60.
3 Bravo-Marquez, F., Frank, E., Mohammad, S. M., and Pfahringer, B. (2016). Determining word-emotion associations from tweets by multilabel classification. In Proc. of the IEEE/WIC/ACM WI, pages 536–539.
4 Burnap, P., Williams, M. L., Sloan, L., Rana, O., Housley, W., Edwards, A., Knight, V., Procter, R., and Voss, A. (2014). Tweeting the terror: modelling the social media reaction to the Woolwich terrorist attack. Social Network Analysis and Mining, 4(1):1–14.
5 De Choudhury, M., Jhaver, S., Sugar, B., and Weber, I. (2016). Social media participation in an activist movement for racial equality. In Proc. of the ICWSM, pages 92–101.
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7 ElSherief, M., Belding, E. M., and Nguyen, D. (2017). # notokay: Understanding gender-based violence in social media. In Proc. of the ICWSM, pages 52–61.
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12 Horgan, J. (2014). The Psychology of Terrorism, Second Edition. Taylor & Francis Group. 2018 SBC 33rd Brazilian Symposium on Databases (SBBD) August 25-26, 2018 - Rio de Janeiro, RJ, Brazil 107
13 Kim, S., Bak, J., Jo, Y., and Oh, A. (2011). Do You Feel What I Feel ? Social Aspects of Emotions in Twitter Conversations. NIPS Workshop, pages 495–498.
14 Kim, Y. (2014). Convolutional neural networks for sentence classification. In Proc. of EMNLP, pages 1746–1751.
15 Lerman, K., Arora, M., Gallegos, L., Kumaraguru, P., and Garcia, D. (2016). Emotions, demographics and sociability in twitter interactions. In Proc. of the ICWSM, pages 201–210.
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17 Lotan, G., Graeff, E., Ananny, M., Gaffney, D., Pearce, I., and danah boyd (2011). The arab spring— the revolutions were tweeted: Information flows during the 2011 tunisian and egyptian revolutions. International Journal of Communication, 5(0).
18 Mitchell, L., Frank, M. R., Harris, K. D., Dodds, P. S., and Danforth, C. M. (2013). The geography of happiness: Connecting twitter sentiment and expression, demographics, and objective characteristics of place. PLOS ONE, 8(5):1– 15.
19 Mohammad, S. (2012). #Emotional Tweets. In Proc. of the First Conference on Lexical and Computational Semantics, pages 246–255.
20 Mohammad, S. M. and Turney, P. D. (2013). Crowdsourcing a word-emotion association lexicon. 29(3):436–465.
21 Mohammad, S. M., Zhu, X., Kiritchenko, S., and Martin, J. (2015). Sentiment, emotion, purpose, and style in electoral tweets. 51(4):480–499.
22 Munezero, M. D., Montero, C. S., Sutinen, E., and Pajunen, J. (2014). Are they different? affect, feeling, emotion, sentiment, and opinion detection in text. IEEE Transactions on Affective Computing, 5(2):101–111.
23 Purver, M. and Battersby, S. (2012). Experimenting with Distant Supervision for Emotion Classification. Proc. of the 13th Conference of the European Chapter of the Association for Computational Linguistics, pages 482–491.
24 Sakaki, T., Okazaki, M., and Matsuo, Y. (2010). Earthquake shakes twitter users: Real-time event detection by social sensors. In Proc. of the 19th International Conference on World Wide Web, pages 851–860.
25 Suttles, J. and Ide, N. (2013). Distant supervision for emotion classification with discrete binary values. In Gelbukh, A., editor, Computational Linguistics and Intelligent Text Processing, pages 121–136, Berlin, Heidelberg. Springer Berlin Heidelberg.
26 Wan, S. and Paris, C. (2015). Understanding Public Emotional Reactions on Twitter. Proc. of ICWSM, pages 715–716.
27 Wang, W., Chen, L., Thirunarayan, K., and Sheth, A. P. (2012). Harnessing twitter ”big data” for automatic emotion identification. In 2012 International Conference on Privacy, Security, Risk and Trust, pages 587–592.