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Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/431
Title: Impact of tweets on Indian movies performance: An integrative approach using sentiment analysis and emotion detection
Authors: Sarin, Gaurav
Agarwal, Rhythm
Goyal, Ekta
Keywords: Artificial Intelligence
Sentiment Analysis
Issue Date: 2023
Abstract: Due to social media's rapid growth, moviegoers primarily rely on internet reviews before buying. Studios must determine how reviews affect sales. This study examines how online reviews affect movie box office earnings using sentiment analysis and emotion recognition. Text reviews affect attendance and revenue as much as rating does. This data can help filmmakers and advertising target demographics. Films met audience expectations, with increased trust and happiness and lower wrath, surprise, disgust, and sadness. However, some films scored better for specific emotions, suggesting they elicited different audience responses. Most film tweets were happier and more trusting after release than before. However, tweets about some films showed more wrath and dread, suggesting marketing or audience reception concerns.
Description: The rapid growth of various social media platforms has enabled consumers to share product experiences and specifics online. According to research, prior to making a purchase decision, consumers peruse online reviews. Due to brief life cycles, the film industry is extremely competitive. The film's genre, director, actors, and plot summary, as well as the marketing techniques used to advertise the film, can all influence box-office earnings. Most prospective moviegoers read movie evaluations, and electronic word of mouth (eWOM) influences box office success (Lee & Choeh, 2018). Nevertheless, movie evaluations contain a wealth of information regarding the perspectives of moviegoers. Numerous studies used sentiment analysis to determine the overall polarity of a text to determine what consumers were thinking (Hu & Chen, 2016; Hu et al., 2018; Liu, B., 2012)
URI: http://localhost:8080/xmlui/handle/123456789/431
Appears in Collections:PGDM

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