Politics is an area that traditionally believed to be gender divided. According intergroup communication theory, this gender-salient context might cause differences in political communications between genders. Moreover, the internet and social media, which creates a computer-mediated interactive context, also impact traditional discrepancies discourse. This study used Twitter trace-data computational text analysis examine such suppositions. By analyzing over one million tweets, we found...

The U.S. confronts an unprecedented public health crisis, the COVID-19 pandemic, in presidential election year 2020. In such a compound situation, real-time dynamic examination of how general ascribe crisis responsibilities taking account to their political ideologies is helpful for developing effective strategies manage and diminish hostility toward particular groups caused by polarization. Social media, as Twitter, provide platforms public’s COVID-related discourse form, accumulate,...

This study attempts to briefly map the general changes of Chinese masculinities in media over time, and explain why these happened. Through visual content analysis, 471 film posters collected from 1951 2016 are examined findings summarised as follows: 1) men decreasingly depicted manual workers or soldiers, increasingly white-collar urbane; 2) delineated aggressive puissant, gentle civil; 3) show their demand for sexuality; finally, 4) portrayals more diverse. These demonstrate be 'softer',...

Purpose This study develops a computational method to investigate the predominant language styles in political discussions on Twitter and their connections with users' online characteristics. Design/methodology/approach gathers large dataset comprising across various topics from general users. It utilizes an unsupervised machine learning algorithm pre-defined features detect Twitter. Furthermore, it employs multinomial model explore relationships between Findings Through analysis of over...

Two studies were conducted to examine gender differences in the discursive political engagement on Twitter. Study 1 analysed about 5.6 million English tweets regarding nine issues and one non-political issue. It found that, compared with men's tweets, a higher proportion of women's are retweets, that majority retweets originate from men. The results may indicate women have arelatively lower level efficacy and/or sense environmental risk than men when participating discussions They also more...

Using automated content analysis, this research explores the phenomenon of pseudo-events coverage in The New York Times (N = 70,370 articles) from 1980 to 2019. By clarifying operationalization pseudo-events, study introduces as a valuable tool index how different social subsystems perpetuate mediatization (which is when institutions absorb and abide by media logic). Machine-learning classifiers were constructed measure which provides historicity, specificity, measurability — three tasks set...

Research about self-branding is mainly drawn from two areas: marketing research and cultural studies. Although they use the same terms—self-branding or personal branding—they sometimes refer to different phenomena, which can lead confusion. Marketing studies usually regard as a strategy that individuals adopt promote their professional careers, while consider immaterial labor associated with consumerism implies hierarchy inequality. Therefore, this essay aims explicate concept of in digital...

Recently deep learning methods have achieved great success in understanding and analyzing text messages. In real-world applications, however, labeled data are often small-sized imbalanced classes due to the high cost of collection human annotation, limiting performance classifiers. Therefore, this study explores an understudied area—how sample sizes imbalance ratios influence models augmentation methods—and provides a solution problem. Specifically, examines BERT, Word2Vec, WordNet with BERT...

Political partisanship constitutes a pivotal group identity that significantly influences individuals’ voting behaviors and shapes their ideological cultural perspectives. While traditional surveys experimental studies can directly capture political by asking the participants, this task has become intricate when employing digital trace data sourced from social media. Previous classification methods, attempting to infer users’ networks or textual content, suffered limited efficiency...

Using automated content analysis, this research explores the phenomenon of pseudo-events coverage in The New York Times (N = 70,370 articles) from 1980 to 2019. By clarifying operationalization pseudo-events, study introduces as a valuable tool index how different social subsystems perpetuate mediatization (which is when institutions absorb and abide by media logic). Moreover, constructed machine-learning classifier measure which provides historicity, specificity, measurability — three tasks...

Entrepreneurship has long represented an academic discipline whose consensual meaning been fragile among many scholars in management, economics or other disciplines within business. That said, over the past two decades come its own, as there exists a critical mass of who have developed shared conception (Astley, 1985). However, we witnessed both shifts topics that entrepreneurship study and journal outlets they target. In addition, review research also revealed new emerged become prominent....

Politeness plays a key role in social communications. Previous work proposed an SVM-based computational method for predicting politeness using linguistic features on corpus that contains Wikipedia and Stack Exchange requests data. To extend this prior work, we focus evaluating the performance of state-of-the-art language models prediction same dataset. Two are applied study. First, fine-tune BERT data then use fine-tuned model prediction. Second, ChatGPT to predict politeness. The results...