Barack Obama

2021 ◽  
pp. 81-110
Author(s):  
Joshua M. Scacco ◽  
Kevin Coe

This chapter analyzes Barack Obama’s administration in relation to the components of the ubiquitous presidency, especially how Obama adapted to the changing contexts of accessibility, personalization, and pluralism. It first tracks Twitter attention to Obama across seven years of his presidency, showing how attention spiked in relation to both traditional major addresses and newer approaches (e.g., his own tweets emphasizing elements of the ubiquitous presidency). The chapter then analyzes West Wing Week, a web series pioneered by the first official White House videographer, which takes the form of reality television and reveals the “backstage” of the presidency. Finally, the chapter uses semantic network analysis to track the relationship between the president, the press, and the public on Twitter in the context of the Affordable Care Act (commonly known as Obamacare). These relationships conform to the cascading activation model, in which presidential communication influences the terms used by the press and the public.

2021 ◽  
pp. 111-142
Author(s):  
Joshua M. Scacco ◽  
Kevin Coe

This chapter analyzes Donald Trump’s administration in relation to the components of the ubiquitous presidency, especially how Trump sought visibility and control amid the contexts of accessibility, personalization, and pluralism. It first tracks Trump’s use of MAGA rallies to narrowcast messages to partisans, and then how he commanded attention via Twitter. On Twitter, Trump’s own tweets—as opposed to traditional major addresses, which were more influential in the Obama presidency—were the primary drivers of attention. Paralleling the analysis in Chapter 4, the chapter then uses semantic network analysis to track the relationship between the president, press, and public on Twitter in the context of the Affordable Care Act (Obamacare). These relationships reveal that Trump’s limited communication about the ACA contributed to an inversion of the traditional cascading activation model. Finally, the chapter explores how Trump’s attacks on pluralism promoted anti-social forms of democratic participation and may have even incited violence.


2021 ◽  
Vol 42 (4) ◽  
pp. 457-471
Author(s):  
Sehyeon Oh ◽  
Hyunah Kang

Objectives: This study analyzes how pulic awareness of perception of child abuse and the recent child abuse policy changes appeared in the news comments about child abuse. The major policy changes include the Act on Special Cases Concerning The Punishment, Etc. of Child Abuse Crimes (Act No. 15255, Dec. 19, 2017), Mandatory CCTV Installation at Daycare Centers (2015), investigation for school children who have been absent school long-term (2016), the 100 state tasks in inclusive welfare (2017), e-Child Happiness Support Service (2018), and Strengthening the Publicness of Child Protection Service (2019).Methods: For the purpose, this study analyzed 1,333,677 comments on news about child abuse from 1 January 2014 to 31 December 2019. In this study, we conducted semantic network analysis to analyze how the contents of child abuse appeared in child abuse comments and the policy contents appeared at the time when major policies were implemented. The analysis using R program.Results: As a result of the analysis, the study found that the public recognized child abuse as a crime. Second, stereotypes on the perpetrators of child abuse were identified. Third, it was confirmed that the public is deeply interested in child abuse incidents occurred at kindergartens and daycare centers. Lastly, the result has revealed that the public, in general, does not yet acknowledge changes on the central policy of child abuse.Conclusion: Based on these findings, policy implcations are discussed to make improvements in awareness of child abuse more accessible to the public. Specifically, The government is responsible for solving stereotypes of child abuse, improving trust in daycare centers, and providing information on child care policies to the public.


2019 ◽  
Vol 41 (2) ◽  
pp. 222-242 ◽  
Author(s):  
Christopher Calabrese ◽  
Brittany N. Anderton ◽  
George A. Barnett

Genome editing is an emerging socio-scientific issue. This study uses semantic network analysis to determine the concepts and frames the public is exposed to when seeking information about “genome editing” in Wikipedia and Google. Four frames were identified in Wikipedia: (1) methodology/terminology, (2) applications, (3) common approaches, and (4) DNA repair mechanisms. Three frames were identified in the Google webpages: (1) scientific contributions, (2) applications, and (3) methodology/terminology. Both representations of genome editing focused on technical information rather than social concerns. Most of the words in both networks were neutral in sentiment, suggesting an opportunity for encouraging engagement around this technology.


2021 ◽  
Vol 21 (3) ◽  
pp. 49-60
Author(s):  
Tae Jin Kim ◽  
Mi Ryeong Eum ◽  
Sang Hyun Park

Recently, the government has been increasingly communicating with the public in response to their opinions on state administration and policy projects. To examine the practicality of the public’s suggestions, this study investigated issues by disaster type, based on information from major media channels and comment data from the news. An analysis of the frequency of appearance, text mining (TF-IDF, LDA, and sentiment analysis), and the semantic network was performed by extracting the comment data of articles on the themes of “disaster” and “evacuation,” published from January 2010 to May 2020. The analysis results showed that news articles centered on these themes increased rapidly from 2017. The main disasters in Korea were those of “fire,” “typhoon,” “forest fire,” “radioactivity,” and “earthquake,” in order of enormity. Of the total negative words pertaining to “radioactivity” disasters, 43% were negative-sentiment words, and the semantic network analysis revealed that the terms “typhoon,” “forest fire,” and “earthquake” were connected to “radioactivity” disasters. This study is meaningful as it identifies issues by type of disaster and factors of anxiety expressed by the public using news and comment data, without conducting surveys and interviews.


2018 ◽  
Vol 10 (11) ◽  
pp. 4027 ◽  
Author(s):  
Sung-Won Yoon ◽  
Sae Chung

This paper aims at exploring how conservative and liberal newspapers in South Korea framed PyeongChang 2018 directly. Our research questions addressed four points: first, different attitudes of conservative and liberal newspapers in the PyeongChang news reporting; second, their success and failure in influencing public opinion; third, South Koreans’ perceptions on PyeongChang 2018; and fourth, South Korean public reliance on the newspapers. To investigate the framing differences, we employed a big data analytic method (automated semantic network analysis) with NodeXL (analytic software). Conclusively, we were able to find out four main findings. First, the conservative media showed pessimistic attitudes to the Olympics, and the liberal media did conversely. Second, despite the conservative media’s resourcefulness, they could not succeed in influencing public opinion. Third, the conservative media perceived the Olympics as an undesirable event, but the liberal media did the Olympics as a significant event for further peace promotion. Fourth, the conservative media’s framings did not considerably influence upon the public opinion. As a conclusion, the public are no longer passive recipients of the messages from the media. Instead, they tend to selectively accept the information from the media based on ‘collective intelligence’. This trend provides a significant implication for enhancing the sustainability of the media environment in South Korea.


2016 ◽  
Vol 5 (2) ◽  
pp. 27-41
Author(s):  
Kyung Sik Kim ◽  
Bo Ram Hyun ◽  
Byung Kook Lee ◽  
Mi Ran Jang

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