Assessing Public Political Ideology: A sentiment Analysis

Stack, Cathal (2014) Assessing Public Political Ideology: A sentiment Analysis. Diploma thesis, Dublin, National College of Ireland.

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The culture of today’s world, is one which could be argued to primarily reside online. In day to day life people quickly take to their favourite social networking sites, to share all aspects of their lives. The most banal and mundane activities are shared with the world, in real time, second by second updates, of the latest bite of ham sandwich are posted. This culture of sharing has spread to almost all domains of our lives, be it to sharing achievements, latest discoveries, jokes or anecdotes, and most frequently opinions. According to (Agarwal, Boyi, Owen, & Passonneau, 2011) microblogging sites such as twitter have now become host to a wide spectrum of information. The culture of real time postings has generated a plethora of opinions on current issues, foods, products, and complaints on day to day life. This contemporary sharing culture has borne witness to a vast mine of text data. The text data is rich with potential for exploration by data analysts, on an almost unlimited number of topics. One analytical technique used for the exploration of such data is that of sentiment analysis. To date there has been a number of notable sentiment analysis projects: tweets about movies (Castellanos et al, 2011), reviews about movies (Joshi et al, 2010), tweets about events related to retailers (Duraidhayalu et al, 2012; Grover et al. 2013), reviews about products and services (Liu et al. 2013; Nagarajan et al 2013; Pantangi et al 2013; Sarkar et al. 2013), and real time sports sentiments (Zhao et al, 2013). In this project we are going to apply sentiment analysis to the domain of public political opinion, using the opinions generated by particular television programmes or news event as our sample population. Before outlining how we will categorise political opinion, it’s helpful to start by addressing the question: What is sentiment analysis?

Item Type: Thesis (Diploma)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Divisions: School of Computing > Higher Diploma in Science in Data Analytics
Date Deposited: 12 Dec 2014 16:00
Last Modified: 12 Dec 2014 16:00

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