In widening the range of interactions by means of diversified channels of communication, digital communication provides unprecedented opportunities to interconnect people. In this perspective, the so-called Social Media Networking tools, also known as Social Media, are among the most populated channels within the “Digital Global Village” (adapting a celebrated expression by Marshall McLuhan 1964), which may be studied from both the significance of the medium used and the content provided by digital communities. As a matter of fact, language used in Social Media allows an unprecedented bulk of language contents to be collected and analysed; however, the content shared is extremely fragmented and uncontrolled. A number of general topics discussed via these forms of communication tends to be divisive and sparks off an intense debate both in a real environment and in digital arenas. In this sense, politics is a case in point, though other topics prove to be controversial such as sports or religion. In this case, politicians use Social Media platforms in order to establish direct contact with citizens (seen also as potential voters), somehow overpowering traditional media; with their statements, they also trigger debates which are more likely to be replied by users with disagreeing views. For these reasons, Social Media tend to generate more disapproval-oriented forms of communication; this is why ‘Hate Speech’ has emerged (Miró-Llinares et al 2016; 2018). Within the framework of Social Media Studies, the present analysis focuses on digital interactions that are triggered by real events and make use of a disapproving or linguistically violent and hostile tone. More specifically, this research focuses on Brexit, or the withdrawal of Great Britain from the European Union. This topic has been covered by British politicians both in public debates and in messages posted on Social Media Tools in order to reach an all-encompassing audience. Due to the politically sensitive topics shared, the kind of reaction from digital users is not the one typically expected (i.e. supporting comments); rather, a more violent, hateful-based response tends to prevail. In the light of the relevance of the reactions by users to such statements and using a completely reversed (and out-of-the-box) perspective, the actual object of analysis is represented by the reactions (in terms of digital verbal acts – or simple comments/reactions) provided by “common” users. More specifically, four Brexit-related case studies have been taken into account. The starting point is represented by institutional tweets issued by British politicians; then, users’ public reactions (i.e. tweet-based replies) have been collected, labelled aspositive/negative in terms of reaction to the tweets and assembled in a small corpus that has been analysed using word frequency lists and KWIC concordance lines. Results have been primarily analysed as four separate cases, then an aggregated analysis was carried out. In three out of four cases, users’ negativity overwhelmed positive reactions (77.90 – 91.93% of occurrences), while positive-based reactions peaked at 51.06%. A corpus-based analysis of hateful comments allowed the identification of grammatical and lexical patterns in which a clear semantic prosody could be inferred. Aggregated results confirmed the significant weight of negative comments (77.74% in a 746-tweet corpus), showing how popular discontent is conveyed through new forms of online discourse.
Thinking out of the box in English Linguistics, Language Teaching, Translation and Terminology
meledandri francesco
2022-01-01
Abstract
In widening the range of interactions by means of diversified channels of communication, digital communication provides unprecedented opportunities to interconnect people. In this perspective, the so-called Social Media Networking tools, also known as Social Media, are among the most populated channels within the “Digital Global Village” (adapting a celebrated expression by Marshall McLuhan 1964), which may be studied from both the significance of the medium used and the content provided by digital communities. As a matter of fact, language used in Social Media allows an unprecedented bulk of language contents to be collected and analysed; however, the content shared is extremely fragmented and uncontrolled. A number of general topics discussed via these forms of communication tends to be divisive and sparks off an intense debate both in a real environment and in digital arenas. In this sense, politics is a case in point, though other topics prove to be controversial such as sports or religion. In this case, politicians use Social Media platforms in order to establish direct contact with citizens (seen also as potential voters), somehow overpowering traditional media; with their statements, they also trigger debates which are more likely to be replied by users with disagreeing views. For these reasons, Social Media tend to generate more disapproval-oriented forms of communication; this is why ‘Hate Speech’ has emerged (Miró-Llinares et al 2016; 2018). Within the framework of Social Media Studies, the present analysis focuses on digital interactions that are triggered by real events and make use of a disapproving or linguistically violent and hostile tone. More specifically, this research focuses on Brexit, or the withdrawal of Great Britain from the European Union. This topic has been covered by British politicians both in public debates and in messages posted on Social Media Tools in order to reach an all-encompassing audience. Due to the politically sensitive topics shared, the kind of reaction from digital users is not the one typically expected (i.e. supporting comments); rather, a more violent, hateful-based response tends to prevail. In the light of the relevance of the reactions by users to such statements and using a completely reversed (and out-of-the-box) perspective, the actual object of analysis is represented by the reactions (in terms of digital verbal acts – or simple comments/reactions) provided by “common” users. More specifically, four Brexit-related case studies have been taken into account. The starting point is represented by institutional tweets issued by British politicians; then, users’ public reactions (i.e. tweet-based replies) have been collected, labelled aspositive/negative in terms of reaction to the tweets and assembled in a small corpus that has been analysed using word frequency lists and KWIC concordance lines. Results have been primarily analysed as four separate cases, then an aggregated analysis was carried out. In three out of four cases, users’ negativity overwhelmed positive reactions (77.90 – 91.93% of occurrences), while positive-based reactions peaked at 51.06%. A corpus-based analysis of hateful comments allowed the identification of grammatical and lexical patterns in which a clear semantic prosody could be inferred. Aggregated results confirmed the significant weight of negative comments (77.74% in a 746-tweet corpus), showing how popular discontent is conveyed through new forms of online discourse.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
