poster

Textual and contextual patterns for sentiment analysis over microblogs

Authors:

Fotis Aisopos,

George Papadakis,

Konstantinos Tserpes,

Theodora VarvarigouAuthors Info & Claims

WWW '12 Companion: Proceedings of the 21st International Conference on World Wide Web

Pages 453 - 454

https://doi.org/10.1145/2187980.2188073

Published: 16 April 2012 Publication History

Get Access

Abstract

Microblog content poses serious challenges to the applicability of sentiment analysis, due to its inherent characteristics. We introduce a novel method relying on content-based and context-based features, guaranteeing high effectiveness and robustness in the settings we are considering. The evaluation of our methods over a large Twitter data set indicates significant improvements over the traditional techniques.

References

[1]

D. Davidov, O. Tsur, and A. Rappoport. Enhanced sentiment learning using twitter hashtags and smileys. In COLING, 2010.

Digital Library

Google Scholar

[2]

J. Eisenstein, B. O'Connor, N. A. Smith, and E. P. Xing. A latent variable model for geographic lexical variation. In EMNLP, 2010.

Digital Library

Google Scholar

[3]

G. Giannakopoulos, V. Karkaletsis, G. A. Vouros, and P. Stamatopoulos. Summarization system evaluation revisited: N-gram graphs. TSLP, 5(3), 2008.

Digital Library

Google Scholar

[4]

L. Jiang, M. Yu, M. Zhou, X. Liu, and T. Zhao. Target-dependent Twitter sentiment classification. In COLING, 2011.

Digital Library

Google Scholar

[5]

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.

Crossref

Google Scholar

[6]

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.

Google Scholar

[7]

J. Yang and J. Leskovec. Patterns of temporal variation in online media. In WSDM, pages 177--186, 2011.

Digital Library

Google Scholar

Cited By

View all

Patil RShrestha A(2019)Feature-Set for Sentiment analysis2019 SoutheastCon10.1109/SoutheastCon42311.2019.9020656(1-5)Online publication date: Apr-2019
https://doi.org/10.1109/SoutheastCon42311.2019.9020656
Kulkarni HAlicea B(2019)Cultural Association based on Machine Learning for Team Formation2019 5th International Conference On Computing, Communication, Control And Automation (ICCUBEA)10.1109/ICCUBEA47591.2019.9129152(1-5)Online publication date: Sep-2019
https://doi.org/10.1109/ICCUBEA47591.2019.9129152
Kulkarni HJoshi TSanap NKalyanpur RMarathe M(2019)Personalized Newspaper Based on Emotional Traits Using Machine Learning2019 5th International Conference On Computing, Communication, Control And Automation (ICCUBEA)10.1109/ICCUBEA47591.2019.9128691(1-5)Online publication date: Sep-2019
https://doi.org/10.1109/ICCUBEA47591.2019.9128691
Show More Cited By

Index Terms

Textual and contextual patterns for sentiment analysis over microblogs
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Language resources
2. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Document filtering
      2. Information extraction

Recommendations

Social sentiment sensor: a visualization system for topic detection and topic sentiment analysis on microblog

As a new form of social media, microblogging provides platform sharing, wherein users can share their feelings and ideas on certain topics. Bursty topics from microblogs are the results of the emerging issues that instantly attract more followers and ...
Integrated microblog sentiment analysis from users' social interaction patterns and textual opinions

Traditional post-level opinion classification methods usually fail to capture a person's overall sentiment orientation toward a topic from his/her microblog posts published for a variety of themes related to that topic. One reason for this is that the ...
Exploiting social relations for sentiment analysis in microblogging
WSDM '13: Proceedings of the sixth ACM international conference on Web search and data mining

Microblogging, like Twitter and Sina Weibo, has become a popular platform of human expressions, through which users can easily produce content on breaking news, public events, or products. The massive amount of microblogging data is a useful and timely ...

Comments

Information & Contributors

Information

Published In

WWW '12 Companion: Proceedings of the 21st International Conference on World Wide Web

April 2012

1250 pages

ISBN:9781450312301

DOI:10.1145/2187980

General Chairs:
Alain Mille
Université de Lyon, France
,
Fabien Gandon
INRIA, France
,
Jacques Misselis
HP, France
,
Program Chairs:
Michael Rabinovich
Case Western Reserve University, USA
,
Steffen Staab
University of Koblenz-Landau, Germany

In-Cooperation

SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 April 2012

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Poster

Conference

WWW 2012

Sponsor:

Univ. de Lyon

WWW 2012: 21st World Wide Web Conference 2012

April 16 - 20, 2012

Lyon, France

Acceptance Rates

Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

7
Total Citations
View Citations
342
Total Downloads

Downloads (Last 12 months)1
Downloads (Last 6 weeks)0

Reflects downloads up to 23 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Patil RShrestha A(2019)Feature-Set for Sentiment analysis2019 SoutheastCon10.1109/SoutheastCon42311.2019.9020656(1-5)Online publication date: Apr-2019
https://doi.org/10.1109/SoutheastCon42311.2019.9020656
Kulkarni HAlicea B(2019)Cultural Association based on Machine Learning for Team Formation2019 5th International Conference On Computing, Communication, Control And Automation (ICCUBEA)10.1109/ICCUBEA47591.2019.9129152(1-5)Online publication date: Sep-2019
https://doi.org/10.1109/ICCUBEA47591.2019.9129152
Kulkarni HJoshi TSanap NKalyanpur RMarathe M(2019)Personalized Newspaper Based on Emotional Traits Using Machine Learning2019 5th International Conference On Computing, Communication, Control And Automation (ICCUBEA)10.1109/ICCUBEA47591.2019.9128691(1-5)Online publication date: Sep-2019
https://doi.org/10.1109/ICCUBEA47591.2019.9128691
Silva ARathnayaka RWijeratne PDeshani MPriyadarshana YKasthurirathna D(2019)Ontological Approach for Aspect-Based Sentiment Analysis2019 IEEE 5th International Conference on Computer and Communications (ICCC)10.1109/ICCC47050.2019.9064483(106-111)Online publication date: Dec-2019
https://doi.org/10.1109/ICCC47050.2019.9064483
Mohammad S(2017)Challenges in Sentiment AnalysisA Practical Guide to Sentiment Analysis10.1007/978-3-319-55394-8_4(61-83)Online publication date: 12-Apr-2017
https://doi.org/10.1007/978-3-319-55394-8_4
Violos JTserpes KPsomakelis EPsychas KVarvarigou T(2016)Sentiment Analysis using Word-GraphsProceedings of the 6th International Conference on Web Intelligence, Mining and Semantics10.1145/2912845.2912863(1-9)Online publication date: 13-Jun-2016
https://dl.acm.org/doi/10.1145/2912845.2912863
Mohammad S(2016)Sentiment AnalysisEmotion Measurement10.1016/B978-0-08-100508-8.00009-6(201-237)Online publication date: 2016
https://doi.org/10.1016/B978-0-08-100508-8.00009-6

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Abstract

References

Cited By

Index Terms

Recommendations

Social sentiment sensor: a visualization system for topic detection and topic sentiment analysis on microblog

Integrated microblog sentiment analysis from users' social interaction patterns and textual opinions

Exploiting social relations for sentiment analysis in microblogging

Comments

Information

Published In

Sponsors

In-Cooperation

Publisher

Publication History

Permissions

Check for updates

Author Tags

Qualifiers

Conference

Acceptance Rates

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

Login options

Full Access

View options

PDF

eReader

Share

Share this Publication link

Share on social media

Affiliations