PC Magazine (06/11/12) Damon Poeter
Researchers at the University of California, Los Angeles and Hewlett-Packard's HP Labs have developed an algorithm that weighs factors such as an article's subject matter and source to determine its likely popularity on Twitter. The algorithm is 84 percent accurate in estimating which news tweets will hit and which will not before the news item itself is actually published. The researchers also were able to determine whether a news article would receive zero retweets with 66 percent accuracy. The news data for the study was collected from a news feed aggregator, and measurements of the spread are performed on Twitter, with the social popularity being determined by the number of times a news URL is posted and shared. To make a prediction, the algorithm considers the news source that generates and posts the article, the category of news the article falls under, the subjectivity of the language in the article, and the named entities mentioned in the article. "Additionally, by comparing with an independent rating of news sources, we demonstrate that there exists a sharp contrast between traditionally popular news sources and the top news propagators on the social Web," the researchers say. The study found that the news source is the most important predictor of an article's popularity.
Researchers at the University of California, Los Angeles and Hewlett-Packard's HP Labs have developed an algorithm that weighs factors such as an article's subject matter and source to determine its likely popularity on Twitter. The algorithm is 84 percent accurate in estimating which news tweets will hit and which will not before the news item itself is actually published. The researchers also were able to determine whether a news article would receive zero retweets with 66 percent accuracy. The news data for the study was collected from a news feed aggregator, and measurements of the spread are performed on Twitter, with the social popularity being determined by the number of times a news URL is posted and shared. To make a prediction, the algorithm considers the news source that generates and posts the article, the category of news the article falls under, the subjectivity of the language in the article, and the named entities mentioned in the article. "Additionally, by comparing with an independent rating of news sources, we demonstrate that there exists a sharp contrast between traditionally popular news sources and the top news propagators on the social Web," the researchers say. The study found that the news source is the most important predictor of an article's popularity.
