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Dissertation
A discourse on Poine, In Search For A Visual Representation Of Pain A Semiotic Perspective
Authors: --- ---
Year: 2016 Publisher: Leuven KU Leuven. Faculteit Letteren

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Abstract

Abstract This thesis aspires to design a “visual sign” that represents pain which can be employed successfully on painkiller packages design. In order to design a sign that conveys the true meaning of pain, first a historical review is presented which reveals how our perception of pain changed over time influenced by cultural understanding, scientific discoveries, and religious beliefs. Current signs of commercial painkiller packages were analysed employing the semiotic theories developed by Greimas, Pierce, and Barthes. These analyses along with quantitative data, acquired by surveys, demonstrated the lack of an adequate sign that represents pain. Considering the painkiller packages as a form of still advertising, Greimas semiotic square was applied to position advertising in the paradigm of informative, persuasive, and/or deceptive. This analysis was applied to top seller painkillers packages. In order to analyse the meaning of the visual sign in the packages, Pierce’s semiotic triad was employed to uncover what messages and meanings are conveyed though the visual sign. The packaging is then analysed using Barthes methodology of Rhetoric of the Image looking at the three messages; iconic and non-iconic, and linguistic denotation and connotation. The inadequacy of pain representation is due to two factors; the first is the incapacity of the language to express such a complex sensation as pain, and therefore, the challenge for pain itself to be represented; the second is the lack of applying semiotics in the process of graphic design, which leads to unthoughtful designs. In our present days, experts and well-known authors differ in their understanding of pain. Although the differences compliment the meanings of pain, they add to its complexity and mythical nature. Inspired by Wittgenstein observation that we learn the language of pain by interacting with adults, and therefore influenced by it, a search for pain language in infants and early childhood was required to better understand the phenomenon. This was conducted through linguistic analysis on CHILDES corpus, the results were employed in a new “visual sign” which then was applied in a new design. The proposed new design was guided by the linguistic and the semiotic analyses which proved to be more successful as evident by quantitative data obtained by a survey.

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Dissertation
Analysis of Social Media Data. Who Is Talking, What Do They Say?
Authors: --- ---
Year: 2017 Publisher: Leuven KU Leuven. Faculteit Wetenschappen

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Social network sites represent an important research area for scholars who are interested in online discourse and its effect on the social and cultural realms. As online social networking usage grow in prevalence, so do psychologists’ concerns about its effects on our society, social development and behaviour online and offline. In this thesis, network analysis and textual analysis will be employed on social media data to understand who are the key-players in a given discussion and what does their discourse reveal. In other words Who is talking and what do they say. The research applies the analyses on a case study, namly hashtag Gamergate (#Gamergate) Twitter data. In brief, the case study hashtag was coined as a revolt against corruption in gaming journalism, and a controversy started after some incidences of women harassment, especially those who are in the gaming industry. In the broadest sense, the controversy created two groups; The anti-Gamergate who believe the hashtag is a women harassment campaign, and the pro-Gamergate who believe the hashtag is against corruption in gaming journalism. In order to achieve the thesis’ goal, the analyses employs distant reading methods on the dataset. First, A Network analysis is conducted to identify key-players in the network. This is achieved by measuring their eigenvector and degree centralities on a time series. Key-players who are persistently ranked high in their centrality measures throughout the whole time (14 months) are chosen for further Analysis. The key-players are then grouped by modularity and confirmed by close reading. Secondly, textual analysis is performed on clusters of key-players’ tweets as one corpus, and all the tweets that “tags” them as another corpus. This is an attempt to compare What do they say, and what is been said about them. The tools employed in the textual analysis include identifying keywords, their collocates, and observe them in their context. The keywords in context provide clues for more close reading research. The research results show the importance of utilizing the combination of network analysis and textual analysis. Furthermore, the vitality of identifying key-players before employing the textual analysis.

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