Sentiment analysis of social media content using N-gram graphs

MM'11 - Proceedings of the 2011 ACM Multimedia Conference and Co-Located Workshops - WSM'11: 3rd ACM Social Media Workshop

Volumn , Issue , 2011, Pages 9-14

  Aisopos, Fotis ^a   Papadakis, George ^a,b   Varvarigou, Theodora ^a  

^a NATIONAL TECHNICAL UNIVERSITY OF ATHENS   (Greece)

^b L3S RESEARCH CENTER   (Germany)

Author keywords

N gram graphs; Polarity classification; Social media

Indexed keywords

AVERAGE DISTANCE; LARGE SCALE EXPERIMENTS; MULTIPLE DOCUMENTS; N-GRAM GRAPHS; N-GRAMS; POLARITY CLASSIFICATION; PUBLIC OPINIONS; REAL WORLD DATA; SENTIMENT ANALYSIS; SOCIAL MEDIA; TECHNICAL CHALLENGES; TEXTUAL PATTERNS;

DATA MINING; VIRTUAL REALITY;

SOCIAL NETWORKING (ONLINE);

EID: 84855364393     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2072609.2072614     Document Type: Conference Paper

References (15)

1. D. Davidov, O. Tsur, and A. Rappoport. Enhanced sentiment learning using twitter hashtags and smileys. In COLING, pages 241-249, 2010.
2. J. Eisenstein, B. O'Connor, N. A. Smith, and E. P. Xing. A latent variable model for geographic lexical variation. In EMNLP, pages 1277-1287, 2010.
3. G. Giannakopoulos, V. Karkaletsis, G. A. Vouros, and P. Stam-atopoulos. Summarization system evaluation revisited: N-gram graphs. TSLP, 5(3), 2008.
4. G. Giannakopoulos and T. Palpanas. Content and type as orthogonal modeling features: a study on user interest awareness in entity subscription services. International Journal of Advances on Networks and Services, 3(2), 2010.
5. A. Go, L. Huang, and R. Bhayani. Twitter sentiment analysis. Entropy, 2009.
6. S. D. Kamvar and J. Harris. We feel fine and searching the emotional web. In WSDM, pages 117-126, 2011.
7. T. Lake and W. Fitzgerald. Twitter sentiment analysis. 2011.
8. C. Manning, P. Raghavan, and H. Schutze. Introduction to information retrieval, volume 1. Cambridge University Press, 2008.
9. B. O'Connor, R. Balasubramanyan, B. R. Routledge, and N. A. Smith. From tweets to polls: Linking text sentiment to public opinion time series. In ICWSM, 2010.
10. A. Pak and P. Paroubek. Twitter as a corpus for sentiment analysis and opinion mining. In LREC, 2010.
11. Y. Tausczik and J. Pennebaker. The psychological meaning of words: Liwc and computerized text analysis methods. Journal of Language and Social Psychology, 29(1):24, 2010.
12. A. Tumasjan, T. O. Sprenger, P. G. Sandner, and I. M. Welpe. Predicting elections with twitter: What 140 characters reveal about political sentiment. In ICWSM, 2010.
13. T. Wilson, P. Hoffmann, S. Somasundaran, J. Kessler, J. Wiebe, Y. Choi, C. Cardie, E. Riloff, and S. Patwardhan. Opinionfinder: A system for subjectivity analysis. In HLT/EMNLP, 2005.
14. I. Witten and E. Frank. Data Mining: Practical machine learning tools and techniques. Morgan Kaufmann Pub, 2005.
15. J. Yang and J. Leskovec. Patterns of temporal variation in online media. In WSDM, pages 177-186, 2011.