With the advancement of internet technology, online news content has become very popular. People can now get live updates of the world's news through online news sites. Social networking sites are also very popular among Internet users, for sharing pictures, videos, news links and other online content. Twitter is one of the most popular social networking and microblogging sites. With Twitter's URL shortening service, a news link can be included in a tweet with only a small number of characters, allowing the rest of the tweet to be used for expressing views on the news story. Social links can be unidirectional in Twitter, allowing people to follow any person or organization and get their tweet updates, and share those updates with their own followers if desired. Through Twitter thousands of news links are tweeted every day.
Whenever there is a popular new story, different news sites will publish identical or nearly identical versions (``clones'') of that story. Though these clones have the same or very similar content, the level of popularity they achieve may be quite different due to content agnostic factors such as influential tweeters, time of publication and the popularities of the news sites. It is very important for the content provider site to know about which factor plays a important role to make their news link popular. In this thesis research, a data set is collected containing the tweets made for the 218 members of 25 distinct sets of news story clones. The collected data is analyzed with respect to basic popularity characteristics concerning number of tweets of various types, relative publication times of clone set members, tweet timing and number of tweeter followers. Then, several other factors are investigated to see their impact in making some news story clones more popular than others. It is found that multiple content-agnostic factors i.e. maximum number of followers, self promotional tweets plays an impact on news site's stories overall popularity, and a first step is taken at quantifying their relative importance.
| Identifer | oai:union.ndltd.org:USASK/oai:ecommons.usask.ca:10388/ETD-2014-01-1376 |
| Date | 2014 January 1900 |
| Contributors | Eager, Derek |
| Source Sets | University of Saskatchewan Library |
| Language | English |
| Detected Language | English |
| Type | text, thesis |
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