2021/07/20 by Tushar Sarkar, Sarkar, Tushar, Nishant Rajadhyaksha +1
Computer Science · #Artificial intelligence #Computation and Language (cs.CL) #Computer science #Data science #Digital Communication and Language #FOS: Computer and information sciences #Geography #Linguistics #Natural Language Processing Techniques #Natural language processing #Process (computing) #Scale (ratio) #Scope (computer science) #Sentiment Analysis and Opinion Mining #Social media #World Wide Web #cs.CL
paper · pdf · doi:10.48550/arxiv.2107.09710
arxiv created 2021/07/20 · openalex publication_date 2021/07/20 · arxiv updated 2021/07/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
Linguistics has been instrumental in developing a deeper understanding of human nature. Words are indispensable to bequeath the thoughts, emotions, and purpose of any human interaction, and critically analyzing these words can elucidate the social and psychological behavior and characteristics of these social animals. Social media has become a platform for human interaction on a large scale and thus gives us scope for collecting and using that data for our study. However, this entire process of collecting, labeling, and analyzing this data iteratively makes the entire procedure cumbersome. To make this entire process easier and structured, we would like to introduce TLA(Twitter Linguistic Analysis). In this paper, we describe TLA and provide a basic understanding of the framework and discuss the process of collecting, labeling, and analyzing data from Twitter for a corpus of languages while providing detailed labeled datasets for all the languages and the models are trained on these datasets. The analysis provided by TLA will also go a long way in understanding the sentiments of different linguistic communities and come up with new and innovative solutions for their problems based on the analysis.