You are here

Corpus Creation for Sentiment Analysis in Code-Mixed Tamil-English Text

Authors: 

Bharathi Raja, Vigneshwaran Muralidaran, Ruba Priyadharshini, John McCrae

Publication Type: 
Refereed Conference Meeting Proceeding
Abstract: 
Understanding the sentiment of a comment from a video or an image is an essential task in many applications. Sentiment analysis of a text can be useful for various decision-making processes. One such application is to analyse the popular sentiments of videos on social media based on viewer comments. However, comments from social media do not follow strict rules of grammar, and they contain mixing of more than one language, often written in non-native scripts. Non-availability of annotated code-mixed data for a low-resourced language like Tamil also adds difficulty to this problem. To overcome this, we created a gold standard Tamil-English code-switched, sentiment-annotated corpus containing 15,744 comment posts from YouTube. In this paper, we describe the process of creating the corpus and assigning polarities. We present inter-annotator agreement and show the results of sentiment analysis trained on this corpus as a benchmark.
Conference Name: 
1st Joint Workshop of SLTU (Spoken Language Technologies for Under-resourced languages) and CCURL (Collaboration and Computing for Under-Resourced Languages) (SLTU-CCURL 2020), co-located with 12th Edition of Language Resources and Evaluation Conference
Proceedings: 
1st Joint Workshop of SLTU (Spoken Language Technologies for Under-resourced languages) and CCURL (Collaboration and Computing for Under-Resourced Languages) (SLTU-CCURL 2020), co-located with 12th Edition of Language Resources and Evaluation Conference
Digital Object Identifer (DOI): 
10.
Publication Date: 
11/05/2020
Conference Location: 
France
Research Group: 
Institution: 
National University of Ireland, Galway (NUIG)
Open access repository: 
Yes