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Articles 1 - 4 of 4
Full-Text Articles in Computer Engineering
Using Textual Features To Predict Popular Content On Digg, Paul H. Miller
Using Textual Features To Predict Popular Content On Digg, Paul H. Miller
Paul H Miller
Over the past few years, collaborative rating sites, such as Netflix, Digg and Stumble, have become increasingly prevalent sites for users to find trending content. I used various data mining techniques to study Digg, a social news site, to examine the influence of content on popularity. What influence does content have on popularity, and what influence does content have on users’ decisions? Overwhelmingly, prior studies have consistently shown that predicting popularity based on content is difficult and maybe even inherently impossible. The same submission can have multiple outcomes and content neither determines popularity, nor individual user decisions. My results show …
Using Textual Features To Predict Popular Content On Digg, Paul H. Miller
Using Textual Features To Predict Popular Content On Digg, Paul H. Miller
Department of English: Dissertations, Theses, and Student Research
Over the past few years, collaborative rating sites, such as Netflix, Digg and Stumble, have become increasingly prevalent sites for users to find trending content. I used various data mining techniques to study Digg, a social news site, to examine the influence of content on popularity. What influence does content have on popularity, and what influence does content have on users’ decisions? Overwhelmingly, prior studies have consistently shown that predicting popularity based on content is difficult and maybe even inherently impossible. The same submission can have multiple outcomes and content neither determines popularity, nor individual user decisions. My results show …
Infoextractor – A Tool For Social Media Data Mining, Chirag Shah, Charles File
Infoextractor – A Tool For Social Media Data Mining, Chirag Shah, Charles File
JITP 2011: The Future of Computational Social Science
We present InfoExtractor, a web-based tool for collecting data and metadata from focused social media content. InfoExtractor then provides this data in various structured and unstructured formats for easy manipulation and analysis. The tool allows social science researchers to easily collect data for quantitative analysis, and is designed to deliver data from popular and influential social media sites in a useful and easy to access way. InfoExtractor was designed to replace traditional means of content aggregation, such as page scraping and brute- force copying.
Data Mining Based Learning Algorithms For Semi-Supervised Object Identification And Tracking, Michael P. Dessauer
Data Mining Based Learning Algorithms For Semi-Supervised Object Identification And Tracking, Michael P. Dessauer
Doctoral Dissertations
Sensor exploitation (SE) is the crucial step in surveillance applications such as airport security and search and rescue operations. It allows localization and identification of movement in urban settings and can significantly boost knowledge gathering, interpretation and action. Data mining techniques offer the promise of precise and accurate knowledge acquisition techniques in high-dimensional data domains (and diminishing the “curse of dimensionality” prevalent in such datasets), coupled by algorithmic design in feature extraction, discriminative ranking, feature fusion and supervised learning (classification). Consequently, data mining techniques and algorithms can be used to refine and process captured data and to detect, recognize, classify, …