We perform sentiment analysis on a new multiclass dataset. We apply various machine learning techniques to this dataset, including Naive Bayes and the Stanford CoreNLP. We then consider various methods for optimizing these algorithms. Finally, we conclude that incorporating syntactical information in our models is vital to the sentiment analysis process.

In this paper, we propose a human-centered framework, “Watching, Thinking, Reacting”, for movie content analysis. The framework consists of a hierarchy of three levels. The low level represents human perception to external stimuli, where the Weber-Fechner Law-based human attention model is constructed to extract movie highlights. The middle level simulates human cognition to semantic, where sem...

This paper analyzes vertical restraints imposed by distributors on movie theaters in the movie exhibition industry. A structural model of industry demand and supply is estimated using a uniquely detailed panel data set of attendance and movie rental contracts collected directly from a sample of U.S. movie theaters. Welfare analysis indicates lifting the restraints would make consumers, movie th...

Hemodynamic activity in occipital, temporal, and parietal cortical areas were recently shown to correlate across subjects during viewing of a 30-minute movie clip. However, most of the frontal cortex lacked between-subject correlations. Here we presented 12 healthy naïve volunteers with the first 72 minutes of a movie ("Crash", 2005, Lions Gate Films) outside of the fMRI scanner to involve the ...

This work aims to use sentiment analysis techniques, data mining, text mining and natural language processing to indicate the polarity of texts using support vector machine. Weka software and a movie review database from Internet Movie Database IMDb were used. This work uses preprocessing filters and WRAPPER techniques and Support Vector Machine (SVM) for classification. It presents better resu...

BACKGROUND Most behavioral approaches to adolescent smoking address the behavior directly. We explore an indirect approach: modifying exposure to portrayals of smoking in movies. OBJECTIVES To describe adolescents' exposure to smoking in movies and to examine factors that could modify such exposure. DESIGN Occurrences of smoking were counted in each of 601 popular movies. Four thousand nine...

We measured long-term memory for a narrative film. During the study session, participants watched a 27-min movie episode, without instructions to remember it. During the test session, administered at a delay ranging from 3 h to 9 mo after the study session, long-term memory for the movie was probed using a computerized questionnaire that assessed cued recall, recognition, and metamemory of movi...

Nowadays, we can observe the applications of machine learning in every field, ranging from quality testing materials to building powerful computer vision tools. One such recent application is recommendation system, which a method that suggests products users based on their preferences. In this paper, our focus specific system called movie recommendation. Here, make use user reviews movies order...