Full Seminar Details

Hassan Saif

KMi, The OpenUniversity

 Hassan Saif
SentiCircles for Contextual and Conceptual Semantic Sentiment Analysis of Twitter
This event took place on Wednesday 14 May 2014 at 11:30


Lexicon-based approaches to Twitter sentiment analysis are gaining much popularity due to their simplicity, domain independence, and relatively good performance. These approaches rely on sentiment lexicons, where a collection of words are marked with fixed sentiment polarities. However, words' sentiment orientation (positive, neural, negative) and/or sentiment strengths could change depending on context and targeted entities. In this paper we present SentiCircle; a novel lexicon-based approach that takes into account the contextual and conceptual semantics of words when calculating their sentiment orientation and strength in Twitter. We evaluate our approach on three Twitter datasets using three different sentiment lexicons. Results show that our approach significantly outperforms two lexicon baselines. Results are competitive but inconclusive when comparing to state-of-art SentiStrength, and vary from one dataset to another. SentiCircle outperforms SentiStrength in accuracy on average, but falls marginally behind in F-measure.

Watch the webcast replay >>

Jobs

Junior Front-end and CMS Web Developer

Knowledge Media Institute (KMi)
21,843 - 24,565
Based in Milton Keynes
Temporary contract for 12 months

The Knowledge Media Institute (KMi) within STEM is looking for a Junior Front-end & CMS Web Developer to join their team at the OU that runs a large aggregator of research papers called CORE, and a set of projects promoting principles of Open...

CONTACT US

Knowledge Media Institute
The Open University
Walton Hall
Milton Keynes
MK7 6AA
United Kingdom

Tel: +44 (0)1908 653800

Fax: +44 (0)1908 653169

Email: KMi Support

COMMENT

If you have any comments, suggestions or general feedback regarding our website, please email us at the address below.

Email: KMi Development Team