چكيده
In the age of widespread usage of social media, millions of users around the world use this easy accessible public platform. People from different cultural background can express their ideas and communicate easily. Since the nature of Computer Mediated Communication allows people to communicate anonymously, this improvement at the same time has a dark side. Anonymity in CMC results in anti-social online behavior, and other de-individuating effects; as a result, giving rise to a phenomenon called hate speech. Hate speech refers to all forms of expressions that aim to spread, promote, or justify hatred, against a specific group or some individuals. Moreover, it is associated with intolerance, discrimination, hatred, hostility, ethnocentrism, and aggression, which makes it a highly emotional term. While studies devoted to hate speech have been increasing in number, only little attention has been paid to how hate speech can be viewed as a reaction against political speech. The aim of this cross-cultural study is to investigate the strategies that Persian and English social network users employed to express hate speech in their online comments in Twitter. The corpus consisted of comments posted in response to politicians' tweets about Iran's nuclear deal posted during June, 2018 to July, 2019. The data were collected manually through Twitter search engine and its advanced research tool which allows accessing past tweets that match the purpose of this study. The data consisted of 10 twitter posts that randomly were selected from Iranian and American politicians' tweets. Social network users can create threads under the tweets and other users can add comments under these threads. After collecting 1000 comments (500 in each corpus), and excluding videos, the images and non-relevant comments, 427 comments in Persian corpus and 393 comments in English corpus remained. After that all the online comments were analyzed according to the coding scheme that emerged from the data. The results of data analysis showed that these strategies were employed in online comments: hatred, criticism (in forms of direct and indirect and their subcategories), humor (in forms of putdown and sarcasm) and swearing. The content analysis demonstrated that the amount of using, hatred, criticism (in this case direct criticism) in form of disapproval and swearing in Persian corpus were greater than English corpus. Overall findings showed that the amount of using direct strategies in Persian corpus were significantly more than English corpus. As the numbers of English language learners who use social networks for a variety of purposes are increasing, knowing cultural differences will help English language learners to develop their communication competence and develop the skill of critical thinking on the content of hate speech. Furthermore, the findings of this cross-culturally CMC-based study will help translators to be aware of the strategies of dealing with hate speech as they play an influential role in the context of mediating hate speech.
