Global Surveillance of COVID-19 by mining news media using a multi-source dynamic embedded topic model

Development of the Brahmaputra River, which links China, India and Bangladesh, has been hindered by significant challenges, particularly political challenges. News reports can mirror the perceptions of political actors, but are, owing to the complexity of the issue, complicated and unstructured. We present a comparative content analysis of the overall framing in news reports of the Brahmaputra River development from major English news media. A structural topic model is established to discover latent topics in the corpus of 1,569 news articles published in 34 countries or regions. We find that politics, including domestic and international politics, dominates the news narratives. Environmental issues, such as glacier status and climate change impacts, are secondarily discussed. Technology and economy issues are less frequently presented in the media coverage. Advantages of upstream countries and dependences of downstream countries are reflected in news reporting and explicitly emerge in the structural topic model. These findings and implications are important for promoting mutual understanding and cooperation among riparian countries in developing the Brahmaputra River. The proposed approach is expected to be widely used as a methodological strategy in future water policy studies.

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News media framing of social protests around racial tensions during the Donald Trump presidency

Journalism ◽

10.1177/14648849211036622 ◽

2021 ◽

pp. 146488492110366

Author(s):

Yotam Ophir ◽

Devin K Forde ◽

Madison Neurohr ◽

Dror Walter ◽

Virginia Massignan

Keyword(s):

News Media ◽

Topic Model ◽

Past Research ◽

Media Framing ◽

Computational Method ◽

News Frames ◽

Political Implications ◽

Depth Analysis ◽

Social Protests ◽

The Right

Media framing of social protests can influence public opinion and governmental response. An extensive line of scholarly work had pointed to the existence of two alternative news frames; public order and debate. We argue that prior work may have been limited by the reliance on deductive strategies using predefined, theoretically-driven frames. Using a data-driven computational method, the Analysis of Topic Model Networks (ANTMN), we examine mainstream news’ framing of two contentious protests that took place during Donald Trump’s presidency; Unite the Right rally in Charlottesville, VA ( n = 1231 news articles), and the Black Lives Matter protests ( n = 2810). In addition to the frames found in past research, we identify a prominent Politics frame, often focussing on the role of Trump in inciting and reacting to racial tensions. An in-depth analysis of the application of frames to each protest revealed a nuanced use of the Protest Paradigm. We suggest possible revisions to existing theories, and discuss the potential social and political implications of our findings.

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Do Not Blame the Media! The Role of Politicians and Parties in Fragmenting Online Political Debate

The International Journal of Press/Politics ◽

10.1177/19401612211015122 ◽

2021 ◽

pp. 194016122110151

Author(s):

Raphael Heiberger ◽

Silvia Majó-Vázquez ◽

Laia Castro Herrero ◽

Rasmus K. Nielsen ◽

Frank Esser

Keyword(s):

Digital Media ◽

News Media ◽

Common Ground ◽

Topic Model ◽

Political Systems ◽

Political Debate ◽

National Elections ◽

Political Actors ◽

The Media ◽

Media Systems

Democratic politics builds on both clear differences and shared common ground. While the rise of digital media may have enabled more differences to be articulated, common ground is often seen as threatened by fragmentation of political debate, which some see as driven by news media. The relative importance of political actors (parties and politicians) in driving fragmentation has received less attention. In this paper, we compare how news media and political actors contribute to the fragmentation of online political debate on the basis of analysis of almost half a million election-related tweets collected during the 2017 French, German, and U.K. national elections. We employ a structural topic model to reduce online political debate to networks of topic overlap. Across the three countries with different political and media systems, we find news media are by far the most important actors in terms of creating and maintaining a common space of online political debate on Twitter. Our results also show that political actors, with some variation from country to country, contribute more to fragmentation as they focus on different topics while articulating clear differences. These findings underline the importance of complementing structural analysis of the rise of digital and social media with analysis of how important elite actors like news media and political parties/candidates use these media in different ways. Overall, we show how at least on Twitter, across three different countries with different media systems and political systems, news media create connection that contributes to commonality while political actors lay out clear differences that drive fragmentation.

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