Movie Data And Social Media Analysis

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Numerous movie data features have been used in models that predict box office revenue. Liu et al. (2016) used features such as the number of theatres in which the movies are released, the popularity of the director (Social media), the popularity of the main actors (Social media), number of tweets released relating to movie and the movie title as search arguments. Du et al. (2014) used weekly box office earnings and microblog data that mentioned movies. Okazaki et al. (2015) used the opening weekend box-office revenue, the last month's search volume and the month before-last one for the movie title in one model and used production budget and the number of screens on which each movie opened. Dellarocas et al. (2004) had features such as budget, number of screens in opening week, the rating of the movie (G, PG, PG13, R, and NR), …show more content…

(2008) used the budget, the marketing costs, US gross, total user posts and average user grade. Karniouchina (2011) focused on using features based on star actors, weekly box office and buzz generated on social media during the week leading up to the release date of a movie. Asur and Huberman (2010) simply used the tweet rate of the movies and the number of theatres that the movies were released in in order to predict box office revenue. Oh et al. (2017) used opening weekend revenue, release type (limited or nationwide) and social media data from Facebook, Twitter and YouTube. Baek et al. (2017) used tweets mentioning movies, blogs mentioning movies, YouTube trailer views and the weekly revenue. When it comes to using data features in prediction models for box office revenue, some features are more widely used by researchers. Features like budget, information on actors and directors, genre and social media data mentioning movies have been used in prediction models for movie box office revenue. For this project, only pre-release data will be used, so using the type of pre-release data that researchers have used would make

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