Skip to main content

2016 | OriginalPaper | Buchkapitel

Sentiment and Behavior Analysis of One Controversial American Individual on Twitter

verfasst von : J. Eliakin M. de Oliveira, Moshe Cotacallapa, Wilson Seron, Rafael D. C. dos Santos, Marcos G. Quiles

Erschienen in: Neural Information Processing

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Social media is a convenient tool for expressing ideas and a powerful means for opinion formation. In this paper, we apply sentiment analysis and machine learning techniques to study a controversial American individual on Twitter., aiming to grasp temporal patterns of opinion changes and the geographical distribution of sentiments (positive, neutral or negative), in the American territory. Specifically, we choose the American TV presenter and candidate for the Republican party nomination, Donald J. Trump. The results acquired aim to elucidate some interesting points about the data, such as: what is the distribution of users considering a match between their sentiment and their relevance? Which clusters can we get from the temporal data of each state? How is the distribution of sentiments, before and after, the first two Republican party debates?

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Thelwall, M., Buckley, K., Paltoglou, G., Cai, D., Kappas, A.: Sentiment in short strength detection informal text. J. Am. Soc. Inf. Sci. Technol. 61(12), 2544–2558 (2010)CrossRef Thelwall, M., Buckley, K., Paltoglou, G., Cai, D., Kappas, A.: Sentiment in short strength detection informal text. J. Am. Soc. Inf. Sci. Technol. 61(12), 2544–2558 (2010)CrossRef
2.
Zurück zum Zitat Prabowo, R., Thelwall, M.: Sentiment analysis: a combined approach. J. Informetrics 3(2), 143–157 (2009)CrossRef Prabowo, R., Thelwall, M.: Sentiment analysis: a combined approach. J. Informetrics 3(2), 143–157 (2009)CrossRef
3.
Zurück zum Zitat Mishra, N., Jha, C.K.: Article: classification of opinion mining techniques. Int. J. Comput. Appl. 56(13), 1–6 (2012) Mishra, N., Jha, C.K.: Article: classification of opinion mining techniques. Int. J. Comput. Appl. 56(13), 1–6 (2012)
4.
Zurück zum Zitat Stieglitz, S., Dang-Xuan, L.: Social media and political communication: a social media analytics framework. Soc. Netw. Anal. Min. 3, 1277–1291 (2012)CrossRef Stieglitz, S., Dang-Xuan, L.: Social media and political communication: a social media analytics framework. Soc. Netw. Anal. Min. 3, 1277–1291 (2012)CrossRef
5.
Zurück zum Zitat Jungherr, A., Jürgens, P., Schoen, H.: Why the pirate party won the german election of 2009 or the trouble with predictions. Soc. Sci. Comput. Rev. 30(2), 229–234 (2012)CrossRef Jungherr, A., Jürgens, P., Schoen, H.: Why the pirate party won the german election of 2009 or the trouble with predictions. Soc. Sci. Comput. Rev. 30(2), 229–234 (2012)CrossRef
6.
Zurück zum Zitat Ringsquandl, M., Petkovic, D.: Analyzing political sentiment on Twitter. In: AAAI Spring Symposium: Analyzing Microtext (2013) Ringsquandl, M., Petkovic, D.: Analyzing political sentiment on Twitter. In: AAAI Spring Symposium: Analyzing Microtext (2013)
7.
Zurück zum Zitat Seron, W., Zorzal, E., Quiles, M.G., Basgalupp, M.P., Breve, F.A.: #Worldcup2014 on Twitter. In: Gervasi, O., Murgante, B., Misra, S., Gavrilova, M.L., Rocha, A.M.A.C., Torre, C., Taniar, D., Apduhan, B.O. (eds.) ICCSA 2015. LNCS, vol. 9155, pp. 447–458. Springer, Heidelberg (2015)CrossRef Seron, W., Zorzal, E., Quiles, M.G., Basgalupp, M.P., Breve, F.A.: #Worldcup2014 on Twitter. In: Gervasi, O., Murgante, B., Misra, S., Gavrilova, M.L., Rocha, A.M.A.C., Torre, C., Taniar, D., Apduhan, B.O. (eds.) ICCSA 2015. LNCS, vol. 9155, pp. 447–458. Springer, Heidelberg (2015)CrossRef
8.
Zurück zum Zitat Soelistio, Y.E., Surendra, M.R.S.: Simple text mining for sentiment analysis of political figure using naive bayes classifier method. CoRR abs/1508.05163 (2015) Soelistio, Y.E., Surendra, M.R.S.: Simple text mining for sentiment analysis of political figure using naive bayes classifier method. CoRR abs/1508.05163 (2015)
9.
Zurück zum Zitat Wang, H., Can, D., Kazemzadeh, A., Bar, F., Narayanan, S.: A system for real-time Twitter sentiment analysis of 2012 U.S. presidential election cycle. In: ACL 2012 System Demonstrations, ACL 2012, pp. 115–120 (2012) Wang, H., Can, D., Kazemzadeh, A., Bar, F., Narayanan, S.: A system for real-time Twitter sentiment analysis of 2012 U.S. presidential election cycle. In: ACL 2012 System Demonstrations, ACL 2012, pp. 115–120 (2012)
10.
Zurück zum Zitat Mejova, Y., Srinivasan, P., Boynton, B.: Gop primary season on Twitter: “popular” political sentiment in social media. In: Sixth ACM International Conference on Web Search and Data Mining, WSDM 2013, pp. 517–526 (2013) Mejova, Y., Srinivasan, P., Boynton, B.: Gop primary season on Twitter: “popular” political sentiment in social media. In: Sixth ACM International Conference on Web Search and Data Mining, WSDM 2013, pp. 517–526 (2013)
11.
Zurück zum Zitat Taheri, S., Mammadov, M., Bagirov, A.M.: Improving naive bayes classifier using conditional probabilities. In: Ninth Australasian Data Mining Conference, AusDM 2011, vol. 121, pp. 63–68 (2011) Taheri, S., Mammadov, M., Bagirov, A.M.: Improving naive bayes classifier using conditional probabilities. In: Ninth Australasian Data Mining Conference, AusDM 2011, vol. 121, pp. 63–68 (2011)
12.
Zurück zum Zitat Morstatter, F., Pfeffer, J., Liu, H., Carley, K.: Is the sample good enough? Comparing data from Twitter’s streaming API with Twitter’s firehose. In: International AAAI Conference on Weblogs and Social Media (2013) Morstatter, F., Pfeffer, J., Liu, H., Carley, K.: Is the sample good enough? Comparing data from Twitter’s streaming API with Twitter’s firehose. In: International AAAI Conference on Weblogs and Social Media (2013)
13.
Zurück zum Zitat Das, S., Chen, M.: Yahoo! for Amazon: extracting market sentiment from stock message boards. In: Asia Pacific Finance Association Annual Conference (APFA) (2001) Das, S., Chen, M.: Yahoo! for Amazon: extracting market sentiment from stock message boards. In: Asia Pacific Finance Association Annual Conference (APFA) (2001)
14.
Zurück zum Zitat Pang, B., Lee, L., Vaithyanathan, S.: Thumbs up?: Sentiment classification using machine learning techniques. In: ACL-02 Conference on Empirical Methods in Natural Language Processing EMNLP, pp. 79–86 (2002) Pang, B., Lee, L., Vaithyanathan, S.: Thumbs up?: Sentiment classification using machine learning techniques. In: ACL-02 Conference on Empirical Methods in Natural Language Processing EMNLP, pp. 79–86 (2002)
16.
Zurück zum Zitat Jiang, L., Wang, D., Cai, Z., Yan, X.: Survey of improving naive bayes for classification. In: Alhajj, R., Gao, H., Li, X., Li, J., Zaïane, O.R. (eds.) ADMA 2007. LNCS (LNAI), vol. 4632, pp. 134–145. Springer, Heidelberg (2007)CrossRef Jiang, L., Wang, D., Cai, Z., Yan, X.: Survey of improving naive bayes for classification. In: Alhajj, R., Gao, H., Li, X., Li, J., Zaïane, O.R. (eds.) ADMA 2007. LNCS (LNAI), vol. 4632, pp. 134–145. Springer, Heidelberg (2007)CrossRef
Metadaten
Titel
Sentiment and Behavior Analysis of One Controversial American Individual on Twitter
verfasst von
J. Eliakin M. de Oliveira
Moshe Cotacallapa
Wilson Seron
Rafael D. C. dos Santos
Marcos G. Quiles
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-46672-9_57