Wisdom of the Crowd Vs Reviews of the Experts: A Case Study Regarding Predicting Movie Box-Office Results
Predicting movie sales figures has been a topic of interest for research for decades since every year there are dozens of movies which surprise investors either in a good or bad way depending on how well the film performs at the box-office compared to the initial expectations. There have been past studies reporting mixed results on using movie critics reviews as one of the sources of information for predicting the movie box-office outcomes. Similarly using social media as a predictor of movie success has been a popular research topic. In this thesis, we perform a case study to evaluate out of two – the (wisdom of the) crowd or the movie critics reviews, which one can predict the outcome of the movies more accurately. We analyze the Hollywood and Bollywood movies from the last three years, which belong to two different geo as well as cultural locations. We used Twitter for collecting the wisdom of the crowd and used movie critics review scores from movie review aggregator sites Metacritic and SahiNahi for Hollywood and Bollywood movies respectively. To perform our evaluation, we extracted various features and used them to build prediction models using different machine learning algorithms. After measuring the performance of prediction models using features from both Twitter and movie critic reviews, we did not find conclusive evidence to declare a clear-cut winner.
Graduation Thesis language
Graduation Thesis type
Master - Computer Science