In this paper, we shall introduce a system for extracting the keyphrases for the reason of authors’ opinion from product reviews. The datasets for two fairly different product review domains related to movies and mobile phones were constructed semiautomatically based on the pros and cons entered by the authors. The system illustrates that the classic supervised keyphrase extraction approach – m...

Many research domains use video contents as stimuli for study on human emotions.A video content within a particular genre or a specific the meevokes dynamic emotions that are highly useful in many research fields. The present study proposed a set of video-clip stimuli that embody four emotions under specific genres of movies, namely happiness, calmness, sadness and fear. Two experiments (a prel...

This paper details our analysis of the Internet Movie Database (IMDb), a free, user-maintained, online resource of production details for over 390,000 movies, television series and video games, which contains information such as title, genre, box-office taking, cast credits and user's ratings. We gather a series of interesting facts and relationships using a variety of data mining techniques. I...

BACKGROUND This study examines the portrayals of soft drinks in popular American movies as a potential vehicle for global marketing and an indicator of covert product placement. METHODS We conducted a content analysis of America's top-ten grossing films from 1991 through 2000 that included portrayals of beverages (95 movies total). Coding reliabilities were assessed with Cohen's kappa, and ex...

We compared the illness narratives of 9 male and 9 female United Kingdom stroke survivors using Frank's typologies of illness narratives. Most respondents presented a single dominant narrative genre ("quest memoir," "restitution," "chaos," or a new "despair" genre); none presented quest manifesto or automythology narratives of social action or self-reinvention. We found no gender differences ap...

In this paper we describe some explorations of the potential of genre-revealing features on automatic sentiment analysis. In particular, we use a small subset of the ‘linguistic facets’ employed in recent experiments on automatic genre identification in combination with more traditional sentiment-revealing features on two different single-genre corpora: a corpus of English blogs and a corpus of...

This paper describes our participation in Genre Tagging Task of MediaEval 2011, which aims to predict the videos’ category label. We use bag-of-words approaches with different features derived from visual content and associated textual information. We perform different experiments in which different constellations in respect of single modalities, classification methods, visual features and thei...

Our project intends to classify movies into the three most probable genres that they belong to, from a predefined set of 25 genres, based on only one image i.e movie poster. We have made use Convolutional Neural Networks (CNN) realize this as we believe it would be help extract features and visual information image. Instead multi-class classification problem in which input is classified any cla...

P innovation is the key revenue driver in the motion picture industry. Because major studios typically launch fewer than 20 movies per year, the financial performance of a single release can have a major effect on the studio’s profitability. In this paper we study how single movie releases impact the investor valuation of the studio. We analyze the change in postlaunch stock price and predict t...

In this paper, we explore complex network properties of word collocation networks (Ferret, 2002) from four different genres. Each document of a particular genre was converted into a network of words with word collocations as edges. We analyzed graphically and statistically how the global properties of these networks varied across different genres, and among different network types within the sa...