ANovel Approach to Analysis of TV Shows usingSocial
Journal Title: The International Journal of Technological Exploration and Learning - Year 2015, Vol 4, Issue 6
Abstract
Television Rating Point (TRP) system is used to measure popularity of Television (TV) shows using people’s meter [1]. Not only does this approach take into account the opinions of a fractional percentage of the audience, but it is also not enough to understand the target audience along various dimensions. In this paper we present a system that uses a novel approach to analyze the audience of a TV show using machine learning, social media and big data technologies. This system will allow TV show producers and potential advertisers to perform sentiment analysis, gender analysis, device analysis of a TV show. Sentiment analysis uses Naïve Bayes Classification [2]. Gender analysis uses data-driven gender determination from name combined with Naïve Bayes Classification. This paper suggests ways to improve on this system to facilitate better insights into the characteristics of the audience of a TV show. This system is economically cheaper to setup, maintain and is easily scalable to accommodate multiple shows and different dimensions of analysis.
Authors and Affiliations
Priyank Jain| B. Tech. (Computer Engineering) Veermata Jijabai Technological Institute (VJTI) Mumbai, Maharashtra, India, Prateek Jakate| B. Tech. (Computer Engineering)Veermata Jijabai Technological InstituteMumbai, Maharashtra, India, Akash Dhotre| B. Tech. (Computer Engineering)Veermata Jijabai Technological InstituteMumbai, Maharashtra, India, Jigar Bhati| B. Tech. (Computer Engineering)Veermata Jijabai Technological InstituteMumbai, Maharashtra, India
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