Research Catalog

Title

Semantic sentiment analysis in social streams / Hassan Saif.

Author

Saif, Hassan

Publication

Amsterdam, Netherlands : IOS Press ; Berlin, Germany : Akademische Verlagsgesellschaft, 2017.

Items in the Library & Off-site

Details

Description

xxii, 286 pages; 24 cm

Summary

Microblogs and social media platforms are now considered among the most popular forms of online communication. Through a platform like Twitter, much information reflecting people?s opinions and attitudes is published and shared among users on a daily basis. This has recently brought great opportunities to companies interested in tracking and monitoring the reputation of their brands and businesses, and to policy makers and politicians to support their assessment of public opinions about their policies or political issues.0A wide range of approaches to sentiment analysis on social media, have been recently built. Most of these approaches rely mainly on the presence of affect words or syntactic structures that explicitly and unambiguously reflect sentiment. However, these approaches are semantically weak, that is, they do not account for the semantics of words when detecting their sentiment in text.0In order to address this problem, the author investigates the role of word semantics in sentiment analysis of microblogs. Specifically, Twitter is used as a case study of microblogging platforms to investigate whether capturing the sentiment of words with respect to their semantics leads to more accurate sentiment analysis models on Twitter.

Series Statement

Studies on the semantic web ; 30

Uniform Title

Studies on the Semantic Web ; 30.

Subject

• Semantic computing
• Social media
• Social Media
• Informatique sémantique
• Médias sociaux
• social media

Bibliography (note)

• Includes bibliographical references.

Processing Action (note)

• committed to retain

ISBN

• 9781614997504
• 1614997500

OCLC

• 1024161409
• SCSB-11516964

Owning Institutions

Harvard Library