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Extant Textual Analysis Essay

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The last parliamentary election in Kuwait was held on July 28th of 2013. The call for candidates to declare their candidacy was announced 40 days earlier. WC represented 3% of the total candidates (8 out of 310). The Kuwaiti tweets posted over those 40 days were searched and retrieved using a Twitter search through the analytics engine of Topsy.com. This search engine stores all tweets posted since 2006. The names of the eight WC were the search keywords. We retrieved 1520 tweets, in addition to the tweets posted by the WC themselves, which were separated from the rest of the tweets. The majority of previous research which has analyzed sentiment towards political candidates on Twitter has selected particular pre-election periods as a time …show more content…

Luckily, we did not come up with any accounts that are accessible only for followers. In previous research, the gender of Twitter users was identified through the user’s first name (Bamman, et al. 2014; Burger, et al. 2011 & Cunha, et al. 2014). However, using only the first name to infer the gender of a Twitter user was not an option for the present study, as it is not uncommon for Kuwaiti Twitter users, especially women, to use pseudonyms as their user names. The tweets (unit of analysis) were analyzed in order to identify the components of both positive and negative attitudes towards the WC. This unit was coded into three categories: positive, neutral and negative. The coders read each tweet as a whole in order to determine whether it was in favor of a candidate, against her, or just making a neutral reference to her. Neutral references included such things as posting a link to a news story in traditional media, quoting a candidate, and posting an announcement for a candidate’s rally or media appearance. Although such tweets could have been representative of a positive leaning towards a candidate, we focused our analysis only on the explicit, verbalized political expressions of the tweeters. All tweets were coded according to the main theme of the opinions expressed. When a tweet had more than one theme, each

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