Skip to main content

2015 | OriginalPaper | Buchkapitel

Sentiment Classification: An Approach for Indian Language Tweets Using Decision Tree

verfasst von : Sudha Shanker Prasad, Jitendra Kumar, Dinesh Kumar Prabhakar, Sukomal Pal

Erschienen in: Mining Intelligence and Knowledge Exploration

Verlag: Springer International Publishing

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

search-config
loading …

Abstract

This paper describes the system we used for Shared Task on Sentiment Analysis in Indian Languages (SAIL) Tweets, at MIKE-2015. Twitter is one of the most popular platform which allows users to share their opinion in the form of tweets. Since it restricts the users with 140 characters, the tweets are actually very short to carry opinions and sentiments to analyze. We take the help of a twitter training dataset in Indian Language (Hindi) and apply data mining approaches for analyzing the sentiments. We used a state-of-the-art Data Mining tool Weka to automatically classify the sentiment of Hindi tweets into positive, negative or neutral.

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 Bautin, M., Vijayarenu, L., Skiena, S.: International sentiment analysis for news and blogs. In: ICWSM (2008) Bautin, M., Vijayarenu, L., Skiena, S.: International sentiment analysis for news and blogs. In: ICWSM (2008)
2.
Zurück zum Zitat Das, A., Bandyopadhyay, S.: Sentiwordnet for indian languages, pp. 56–63. Asian Federation for Natural Language Processing, China (2010) Das, A., Bandyopadhyay, S.: Sentiwordnet for indian languages, pp. 56–63. Asian Federation for Natural Language Processing, China (2010)
3.
Zurück zum Zitat Das, D., Bandyopadhyay, S.: Word to sentence level emotion tagging for bengali blogs. In: Proceedings of the ACL-IJCNLP 2009 Conference Short Papers, pp. 149–152. Association for Computational Linguistics (2009) Das, D., Bandyopadhyay, S.: Word to sentence level emotion tagging for bengali blogs. In: Proceedings of the ACL-IJCNLP 2009 Conference Short Papers, pp. 149–152. Association for Computational Linguistics (2009)
4.
Zurück zum Zitat Das, D., Bandyopadhyay, S.: Labeling emotion in bengali blog corpus-a fine grained tagging at sentence level. In: Proceedings of the 8th Workshop on Asian Language Resources, p. 47 (2010) Das, D., Bandyopadhyay, S.: Labeling emotion in bengali blog corpus-a fine grained tagging at sentence level. In: Proceedings of the 8th Workshop on Asian Language Resources, p. 47 (2010)
5.
Zurück zum Zitat Das, S., Chen, M.: Yahoo! for amazon: extracting market sentiment from stock message boards. In: Proceedings of the Asia Pacific Finance Association Annual Conference (APFA), vol. 35, p. 43, Bangkok, Thailand (2001) Das, S., Chen, M.: Yahoo! for amazon: extracting market sentiment from stock message boards. In: Proceedings of the Asia Pacific Finance Association Annual Conference (APFA), vol. 35, p. 43, Bangkok, Thailand (2001)
6.
Zurück zum Zitat Ghosh, A., Li, G., Veale, T., Rosso, P., Shutova, E., Reyes, A., Barnden, J.: Semeval-2015 task 11: sentiment analysis of figurative language in twitter. In: International Workshop on Semantic Evaluation (SemEval-2015) (2015) Ghosh, A., Li, G., Veale, T., Rosso, P., Shutova, E., Reyes, A., Barnden, J.: Semeval-2015 task 11: sentiment analysis of figurative language in twitter. In: International Workshop on Semantic Evaluation (SemEval-2015) (2015)
7.
Zurück zum Zitat Liu, B.: Sentiment analysis and subjectivity. In: Handbook of Natural Language Processing, vol. 2, pp. 627–666 (2010) Liu, B.: Sentiment analysis and subjectivity. In: Handbook of Natural Language Processing, vol. 2, pp. 627–666 (2010)
8.
Zurück zum Zitat Pang, B., Lee, L.: Seeing stars: exploiting class relationships for sentiment categorization with respect to rating scales. In: Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics, pp. 115–124. Association for Computational Linguistics (2005) Pang, B., Lee, L.: Seeing stars: exploiting class relationships for sentiment categorization with respect to rating scales. In: Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics, pp. 115–124. Association for Computational Linguistics (2005)
9.
Zurück zum Zitat Pang, B., Lee, L., Vaithyanathan, S.: Thumbs up?: sentiment classification using machine learning techniques. In: Proceedings of the ACL-2002 Conference on Empirical Methods in Natural Language Processing, vo. 10, pp. 79–86. Association for Computational Linguistics (2002) Pang, B., Lee, L., Vaithyanathan, S.: Thumbs up?: sentiment classification using machine learning techniques. In: Proceedings of the ACL-2002 Conference on Empirical Methods in Natural Language Processing, vo. 10, pp. 79–86. Association for Computational Linguistics (2002)
10.
Zurück zum Zitat Patra, B.G., Das, D., Das, A., Prasath, R.: Shared task on sentiment analysis in indian languages (sail) tweets - an overview. In: Proceeding of the Mining Intelligence and Knowledge Exploration (MIKE-2015) (2015) Patra, B.G., Das, D., Das, A., Prasath, R.: Shared task on sentiment analysis in indian languages (sail) tweets - an overview. In: Proceeding of the Mining Intelligence and Knowledge Exploration (MIKE-2015) (2015)
11.
Zurück zum Zitat Quinlan, J.R.: C4. 5 Programs for Machine Learning. Elsevier, New York (2014) Quinlan, J.R.: C4. 5 Programs for Machine Learning. Elsevier, New York (2014)
12.
Zurück zum Zitat Sharma, S., Agrawal, J., Sharma, S.: Classification through machine learning technique: C4. 5 algorithm based on various entropies. Int. J. Comput. Appl. 82(16), 28–32 (2013) Sharma, S., Agrawal, J., Sharma, S.: Classification through machine learning technique: C4. 5 algorithm based on various entropies. Int. J. Comput. Appl. 82(16), 28–32 (2013)
13.
Zurück zum Zitat Silva, N.F., Hruschka, E.R., Hruschka Jr, E.R.: Biocom usp: tweet sentiment analysis with adaptive boosting ensemble. In: SemEval 2014, p. 123 (2014) Silva, N.F., Hruschka, E.R., Hruschka Jr, E.R.: Biocom usp: tweet sentiment analysis with adaptive boosting ensemble. In: SemEval 2014, p. 123 (2014)
14.
Zurück zum Zitat Snyder, B., Barzilay, R.: Multiple aspect ranking using the good grief algorithm. In: HLT-NAACL, pp. 300–307 (2007) Snyder, B., Barzilay, R.: Multiple aspect ranking using the good grief algorithm. In: HLT-NAACL, pp. 300–307 (2007)
15.
Zurück zum Zitat Tong, R.M.: An operational system for detecting and tracking opinions in on-line discussion. In: Working Notes of the ACM SIGIR 2001 Workshop on Operational Text Classification, vol. 1, p. 6 (2001) Tong, R.M.: An operational system for detecting and tracking opinions in on-line discussion. In: Working Notes of the ACM SIGIR 2001 Workshop on Operational Text Classification, vol. 1, p. 6 (2001)
16.
Zurück zum Zitat Turney, P.D.: Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews. In: Proceedings of the 40th Annual Meeting on Association For Computational Linguistics, pp. 417–424. Association for Computational Linguistics (2002) Turney, P.D.: Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews. In: Proceedings of the 40th Annual Meeting on Association For Computational Linguistics, pp. 417–424. Association for Computational Linguistics (2002)
17.
Zurück zum Zitat Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann, San Francisco (2005) Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann, San Francisco (2005)
Metadaten
Titel
Sentiment Classification: An Approach for Indian Language Tweets Using Decision Tree
verfasst von
Sudha Shanker Prasad
Jitendra Kumar
Dinesh Kumar Prabhakar
Sukomal Pal
Copyright-Jahr
2015
DOI
https://doi.org/10.1007/978-3-319-26832-3_62