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Predicting Highest Facebook Reaction Count through News Articles

Siddique, Saad (2017) Predicting Highest Facebook Reaction Count through News Articles. Masters thesis, Dublin, National College of Ireland.

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News organizations have been instrumental in holding governments and other powerful figures accountable for their actions. They have change social perspectives and guide their readers towards the desired objectives. The relative decline of traditional media, such as television and paper, that once attracted millions of people, has forced news organizations to shift their focus towards social media to increase viewership. Using `like', share and comment counts to understand the readers has been fruitful, but the news organizations should utilize the new reaction buttons introduced on Facebook. My objective is demonstrate how these news organizations can analyze their own, and their competitors, new articles to predict which highest reaction they are likely to receive. The conclusions drawn from my dissertation is that it is possible. However, caution must be drawn for scenarios when predicting controversial news article.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4150 Computer Network Resources > The Internet > World Wide Web > Websites > Online social networks
T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunications > The Internet > World Wide Web > Websites > Online social networks
Divisions: School of Computing > Master of Science in Data Analytics
Depositing User: Caoimhe Ní Mhaicín
Date Deposited: 28 Aug 2018 08:25
Last Modified: 28 Aug 2018 10:02

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