جستجوی مقالات مرتبط با کلیدواژه « Twitter » در نشریات گروه « ادبیات و زبان ها »

The ever-increasing development of the Internet and the creation of emojis has led to the emergence and development of a new language for the new generation of communication and facilitating human interactions in the context of social networks. The purpose of this research was to investigate the types of linguistic functions of emojis on Twitter based on the approach of Haring and Dinas (2017), which was carried out and discussed with the method of quantitative content analysis. By selecting the top three hashtags in each of the social, economic, culture and health fields, 5000 tweets were selected as the statistical population and among them, 1200 tweets were randomly selected from male and female users and in the time frame. Six months from March 1399 to September 1400 were selected as a sample and coded using Maxqda software, the share of each domain was 300 tweets. Based on the results, in total, the tweets had the highest frequency of occurrence in the order of interpretive, emotional, polite, emphatic, structural, communicative and referential functions.

With the spread of coronavirus in Iran, the government cancelled public events and declared the necessity of closing crowded centers, including religious places. Following this announcement, some people in Mashhad and Qom protested by entering the holy shrines. These actions were quickly reflected in cyberspace. On twitter- a social networking Web site- which is possible for the users to debate, A group of users considered the opposition to health orders contrary to religious law. Another group contrasted religion with science. The present study aims to study these debates and the main question is that what strategies each group used to express its beliefs and viewpoints? For this purpose, 170 Persian tweets containing the keywords "religion" and "corona" were selected and examined using the Van Dijk Model. Data analysis showed that the most common linguistic tools used by users to represent their beliefs and ideologies are the two strategies of "distancing" and "cursing". Since the role and the influence of social networks, e.g., Twitter, are undeniable and tweets can shape social actions, the conflict observed in this space can also extend to the community and cause tensions. The results of this study and doing similar studies can help to identify the cause of these conflicts and provide the basis for empathy and the possibility of beneficial dialogue between different ideologies and thus ensure social stability.

Due to the importance of Covid19 virus in people's lives in the last few years, the present study aimed to investigate how people expressed their feelings about this disease. In other words, this study explored the type of emotions expressed by people and the topics discussed by them in social networks. To this end, using a configuration-based method, first, 53000 documents were collected using the method of crawling pages from Twitter. The data were then classified automatically using emotional keywords and metaphorical concepts. After that the important issues raised in these data were identified. Topics such as vaccination, complications of coronary disease, and health, cultural, political, economic, religious, educational, and global status have been among the topics raised by users during this period. The results showed that some economic, health, and political issues and complications of coronary heart disease have played a greater role than other issues to express emotions.

This article examines how users' narratives are formed and analyzed in Persian Twitter during the earthquake of Kermanshah in 2017. In addition, the prevalent narratives on Persian Twitter will also be identified in this event to determine which users' stories have been hegemonic on this social media. Given that the narratives formed on Twitter are still a new topic for scholars to research, a plausible theoretical framework cannot be found. For this reason, by first reviewing the views on narratives on Twitter, mainly the structuralist model of Luff and Waltzsky (Ochs and Capps' discussion of narrative qualities and narrative approach) is attempted to provide a good theoretical background for the analysis. Also, using the online platform Discovery Text, 23,964 tweets were collected in the first 24 hours after the Kermanshah earthquake in 2017. Then, 15% of the collected tweets were randomly selected and analyzed relying on the critical analysis method of social media discourse. The results showed that there were three types of narration on Twitter: single narratives, reference narratives, and associative narratives. Each of these narratives is discussed in detail in the paper. The results also showed that the reference narratives and the dominant associative narratives are often critical and political.