User sentiment detection: a YouTube use case

Choudhury, Smitashree and Breslin, John G. (2010). User sentiment detection: a YouTube use case. In: The 21st National Conference on Artificial Intelligence and Cognitive Science, 30 August - 1 September 2010, Galway, Ireland.

Full text available as:

Preview

PDF (Accepted Manuscript) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (175Kb)

URL:	http://aics.nuigalway.ie/index.html
Google Scholar:	Look up in Google Scholar

Abstract

In this paper we propose an unsupervised lexicon-based approach to detect the sentiment polarity of user comments in YouTube. Polarity detection in social media content is challenging not only because of the existing limitations in current sentiment dictionaries but also due to the informal linguistic styles used by users. Present dictionaries fail to capture the sentiments of community-created terms. To address the challenge we adopted a data-driven approach and prepared a social media specific list of terms and phrases expressing user sentiments and opinions. Experimental evaluation shows the combinatorial approach has greater potential. Finally, we discuss many research challenges involving social media sentiment analysis.

Item Type:

Conference Item

The Authors

External Project Funding Details:

Funded Project Name	Project ID	Funding Body
Not Set	Not Set	Science Foundation Ireland under grant number SFI/08/CE/I1380 (Líon 2)

Academic Unit/Department:

Knowledge Media Institute

Item ID:

32459

Depositing User:

Smitashree Choudhury

Date Deposited:

07 Feb 2012 17:27

Last Modified:

26 Oct 2012 16:30

URI:

http://oro.open.ac.uk/id/eprint/32459

Actions (login may be required)

	View Item
	Report issue / request change

Policies | Disclaimer