In this paper we argue that a combination of Actor-Network Theory (ANT) and Genre Theory can constitute a theoretical framework for understanding how digital genres evolve. Genre theory states that genres evolve over time through reciprocal interaction between institutionalized practices and individual action; that they develop from actors’ responses to recurrent situations, and are shaped ar...

Abstract We explore a simple, web-based method for predicting the genre of a given artist based on co-occurrence analysis, i.e. analyzing co-occurrences of artist and genre names on music-related web pages. To this end, we use the page counts provided by Google to estimate the relatedness of an arbitrary artist to each of a set of genres. We investigate four different query schemes for obtainin...

the present study investigated the effect of single and multiple genre movies on listening comprehension of upper intermediate language learners. to this end, a language proficiency test was administered to 40 male and female postgraduates of different majors attending international english language testing system (ielts) classes and ultimately 25 upper intermediate language learners were selec...

Under the influence of a new medium, a genre may evolve into variants of the original genre or even into new genre. Genre, even through such evolution, are normally characterized by the tuple, , and little attention is paid to the functionality afforded by the new medium. The combination of the computer and the Internet, however, has resulted in the emergence of cybergenre, a new...

In the ESP tradition, genre is often defined as “structured communicative events engaged in by specific discourse communities whose members share broad communicative purposes.” ESP genre research has generated numerous descriptions and explanations of discipline-specific genre exemplars and has produced various pedagogical proposals. However, what learners learn from these genre descriptions an...

We investigate the uses and limitations of MFCC analysis for feature extraction from music files in the domain of genre recognition. Intra-genre and Inter-genre classification is explored. We implement a method of genre classification based on MFCC extraction, K-means clustering, and KNN analysis. We demonstrate the efficacy of our method through testing, yielding a 99% accuracy rate.

This paper contributes to a facet from the area of Web Information Retrieval that has recently received much attention: The satisfaction of a user’s personal information need with respect to text type, presentation type, or information quality. We imply that such properties can be quantified for all kinds of Web documents, and we subsume them under the term “Web genre” or “genre”. Recent survey...

Existing systems for automatic genre classification follows a supervised framework that extracts genre-specific information from manually-labeled music data and then identifies unknown music data. However, such systems may not be suitable for personal music management, because manually labeling music based on individually-defined genres can be labor intensive and subject to inconsistence from t...