- Home
- A-Z Publications
- Computational Communication Research
- Previous Issues
- Volume 5, Issue 1, 2023
Computational Communication Research - Volume 5, Issue 1, 2023
Volume 5, Issue 1, 2023
Language:
English
-
-
Going Micro to Go Negative?
Authors: Fabio Votta, Arman Noroozian, Tom Dobber, Natali Helberger & Claes de VreeseAbstract Spreading uncivil negative campaign messages is a “high-risk, high reward” campaign strategy since certain voters are more likely to be swayed by negative messaging whereas other voters are more inclined to feel sympathy with the attacked. Due to its risks, campaigns may attempt to outsource their uncivil ads to outside groups thus distancing themselves from the negativity and potentially avoiding any bac Read More
-
-
-
Word Embedding Enrichment for Dictionary Construction: An Example of Incivility in Cantonese
Authors: Hai Liang, Yee Man Margaret Ng & Nathan L.T. TsangDictionary-based methods remain valuable to measure concepts based on texts, though supervised machine learning has been widely used in much recent communication research. The present study proposes a semi-automatic and easily implemented method to build and enrich dictionaries based on word embeddings. As an example, we create a dictionary of political incivility that contains vulgarity and name-call Read More
-
-
-
The speech we miss: How keyword-based data collection obscures youth participation in online political discourse
More LessIn this work, we leverage a panel of over 1.6 million Twitter users matched with public voter records to assess how a standard keyword-based approach to social media data collection performs in the context of participatory politics, and we critically examine the speech this method leaves behind. We find that keyword classifiers undercount young people’s participation in online political discourse, and that valuable political e Read More
-
-
-
Integrating surveys and social media to better understand the dynamics of public opinion
Authors: Maud Reveilhac & Davide MorselliOur study investigates the impact of social media on survey outcomes, particularly focusing on how the general public’s perception of issue importance is influenced by Twitter. To accomplish this, we propose two case studies in Swiss politics focusing on social media’s effect on opinion change during elections and the similarities in arguments on social media and in survey data during direct democracy votes. This study r Read More
-
-
-
Topic Model Validation Methods and their Impact on Model Selection and Evaluation
Authors: Jana Bernhard, Martin Teuffenbach & Hajo G. BoomgaardenTopic Modeling is currently one of the most widely employed unsupervised text-as-data techniques in the field of communication science. While researchers increasingly recognize the importance of validating topic models and given the prevalence of discussions of inadequate validation practices in the literature, there is limited understanding of the consequences of employing different validation strategies when evaluati Read More
-
-
-
Device-Dependent Biases in Mobile Online News
Authors: Mario Haim & Cornelius PuschmannOne in four German internet users claims that search engines are their main gateway to news and a majority of Germans reports to primarily use their smartphone over their laptop/desktop computer to access news online. Yet, search-engine providers such as Google have repeatedly pointed out to actively favor specific forms of technical content optimization for mobile devices (e.g., Accelerated Mobile Pages), raising the que Read More
-
-
-
Media selection is highly predictable, in principle
Authors: Xuanjun Gong & Richard HuskeyMedia research is, in part, interested in accurately explaining and predicting people’s media selection. Explanation is an accurate description of the causal mechanisms that govern media selection whereas prediction is focused on making accurate inferences about unobserved data. However, meta-analyses demonstrate that existing media selection theories and models have limited explanatory accuracy. The predictive accura Read More
-
-
-
Cross-Platform Information Flow and Multilingual Text Analysis: A Comparative Study of Weibo and Twitter Through Deep Learning
Authors: Zituo Wang, Jiayi Zhu, Yixuan Xu, Donggyu Kim & Dmitri WilliamsThis study delved into cross-platform information flow and multilingual text analysis by examining social media posts on Weibo and Twitter in Chinese and English. We investigated public opinions about a violent restaurant attack in China that received widespread attention and validated three strategies of Bidirectional Encoder Representations from Transformers (BERT) to classify multilingual social media posts regarding Read More
-
-
-
Simulating Reputation Dynamics and Their Manipulation: An Agent Based Model Framework
Authors: Torsten Andreas Enßlin, Viktoria Kainz & Céline BoehmReputation is essential to human interactions and shapes group dy- namics, however, it can be manipulated. In order to identify key aspects of malicious communication strategies, we have developed an agent- based simulation framework that captures aspects of the dynamics of social reputation communication: the reputation game simulation. Af- ter giving an overview of our framework, we highlight both previous and Read More
-
-
-
Attraction behind “Beauty”: Revealing Gay Men’s Self-Presentation on a Dating App with Computer Vision
Authors: Jia Fan, Yan Ming Chen, Lun Zhang, Ye Wu & Xiao Fan LiuProfile photos, which are fundamental constructs of online self-presentation, are crucial to building successful online relationships. The visual cues embodied in profile photos are factors that help initiate socialization on visual-based gay dating platforms. This study applies app crawler techniques to collect publicly disclosed profile photos from Finka, a Chinese gay men’s dating app, and uses computer vision artificial int Read More
-
-
-
grafzahl: fine-tuning Transformers for text data from within R
More LessThis paper introduces grafzahl, an R package for fine-tuning Transformers for text data from within R. The package is used in this paper to reproduce the analyses in other papers. Very significant improvement in model accuracy over traditional machine learning approaches such as Convolutional Neural Network is observed.
-
-
-
Automated Detection of Voice in News Text – Evaluating Tools for Reported Speech and Speaker Recognition
Authors: Ahrabhi Kathirgamalingam, Fabienne Lind & Hajo G. BoomgaardenThe automated content analysis of text has become integral to contemporary communication and journalism research. However, automated approaches are seldom utilized to analyze reported voice in text, while doing so would offer valuable insights into media and communication practices. Bridging the fields of communication science and computational linguistics, this study reviews and evaluates off-the-shelf tools Read More
-
-
-
Algorithmic Recommendations’ Role for the Interrelatedness of Counter-Messages and Polluted Content on YouTube – A Network Analysis
Authors: Lisa Zieringer & Diana RiegerCounter-messages are used by civil education, youth prevention actors, and security agencies to counter the magnitude of polluted content. On the Internet, algorithmic operations of intermediaries affect how users encounter and receive polluted content. As counter-messages often show similar keywords, algorithms establish connections between counter-messages and polluted content, primarily because they share mutu Read More
-
-
-
Are we projecting gender biases to ungendered things? Differences in referring to female versus male named hurricanes in 33 years of news coverage
Authors: Ly Dinh, Janina Sarol, Sullam Jeoung & Jana DiesnerHurricanes are ungendered phenomena that are ascribed with gendered names. We examined if news information about the hurricanes are presented using gendered language. This work helps identify if people use gender stereotyping when referring to gender-neutral entities, and what these stereotypes might be. We use methods from natural language processing, qualitative text analysis, and statistics to analyze how g Read More
-
-
-
Political discussions in online oppositional communities in the non-democratic context
More LessTaking into account YouTube’s specific role in the Russian media system and the increasing level of political polarization in the country, this study examines the role of incivility in discussions and whether discussions in an anti-government community represent a place for disagreement between pro-opposition and pro-government users. I argue that an online environment helps these sides meet each other rather than c Read More
-
Most Read This Month
Article
content/journals/26659085
Journal
10
5
false
en
Most Cited Most Cited RSS feed
-
-
Computational observation
Authors: Mario Haim & Angela Nienierza
-
- More Less