The Bully Pulpit, Social Media, and Public Opinion: A Big Data Approach

Gabriel, Michael; Agur, Colin

doi:10.1080/19331681.2018.1485604

Cited by 7 publications

(4 citation statements)

References 38 publications

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“…The festive atmosphere of the holidays, juxtaposed with the negative mood toward the government shutdown and its consequences, made the event ideal to study the element of emotion in the discussion of an event of governance. Many studies have looked at Twitter as a means of probing public opinion (Casas & Wilkerson, 2017; Merchant et al, 2014; Michael & Agur, 2018). The 2018–2019 government shutdown similarly generated a vast discussion on Twitter.…”

Section: Discussionmentioning

confidence: 99%

Actors, Partisan Inclination, and Emotions: An Analysis of Government Shutdown News Stories Shared on Twitter

Agur

Gan

2021

Social Media + Society

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Scholars have recognized emotion as an increasingly important element in the reception and retransmission of online information. In the United States, because of existing differences in ideology, among both audiences and producers of news stories, political issues are prone to spark considerable emotional responses online. While much research has explored emotional responses during election campaigns, this study focuses on the role of online emotion in social media posts related to day-to-day governance in between election periods. Specifically, this study takes the 2018–2019 government shutdown as its subject of investigation. The data set shows the prominence of journalistic and political figures in leading the discussion of news stories, the nuance of emotions employed in the news frames, and the choice of pro-attitudinal news sharing.

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Section: Discussionmentioning

confidence: 99%

Actors, Partisan Inclination, and Emotions: An Analysis of Government Shutdown News Stories Shared on Twitter

Agur

Gan

2021

Social Media + Society

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“…Through its revolutionary virtual platforms, social media has completely transformed the means and ways people interact with each other (Beig and Khan, 2018;Beig and Khan, 2020;Cao et al, 2020;Klobas et al, 2018a, b;Lee et al, 2017;Olanrewaju et al, 2020;Saqib and Amin, 2022). Over the years, the emerging digital upheaval in smartphones, electronic wearable devices, etc., has led billions of people to use social media (Michael and Agur, 2018). Social media users often spend much time on such platforms and post much multimedia content on such networks (Klobas et al, 2018a, b;Leong et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…, 2020; Saqib and Amin, 2022). Over the years, the emerging digital upheaval in smartphones, electronic wearable devices, etc., has led billions of people to use social media (Michael and Agur, 2018). Social media users often spend much time on such platforms and post much multimedia content on such networks (Klobas et al.…”

Section: Introductionmentioning

confidence: 99%

The development and validation of the Indian social media addiction scale

Saqib¹,

Amin²

2023

OIR

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PurposeMillions of social media users over the last two decades have become dependent on social media that has negatively affected their lives, both physically and mentally. Earlier attempts on social media addiction (SMA) scale development have not been made in India which makes it essential to undertake such a study in this region. One of the objectives of this study was to explore and identify the relevant dimensions of the SMA in the literature. The main study objective was to develop and validate a scale on SMA in India.Design/methodology/approachThe research design applied in this work was both qualitative and quantitative. Based on the literature review, some themes of SMA were recognized that were used to conduct semi-structured interviews with the concerned subjects. The interviews conducted were then transcribed, and using NVivo software application, content analysis was carried out. This helped in the identification of relevant themes that were used for preparing the questionnaire. After that an exploratory study was conducted to explore the factors of SMA. This was followed by a confirmatory analysis on a different sample that validated the instrument.FindingsThis work developed and validated a six-factor measure of SMA. The total numbers of items in the final instrument are 22. Salience, Tolerance, Mood Modification, Relapse, Withdrawal and Conflict are the six factors of the final scale.Practical implicationsThe current designed instrument can be exceptionally functional for evaluating the occurrence and level of the SMA. This can also serve to assist in the handling and management of such online addictive behavior. A lot of productivity is lost due to the unwarranted time spent on the social media. By better understanding the dimensions of SMA, one can limit one's time on such networks.Social implicationsThis work can provide valuable insight into this domain and help in understanding and treatment of this malaise. It can also help parents and other stakeholders at large to comprehend the danger linked with the excessive social media use and therefore, contribute towards the society. These dimensions can also help counsellors and psychologists to better understand the addiction behavior and accordingly counsel the concerned individual.Originality/valueAlthough many instruments have been developed in the past by researchers to measure SMA,still some aspects of the concept remain under-researched. Moreover, most of such research has been confined to the developed world regions.

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“…Why Twitter Existing work in political attention relies largely on political speeches (Laver, Benoit, and Garry, 2003;Oliver and Rahn, 2016;Yu, Kaufmann, and Diermeier, 2008;Quinn et al, 2010) and party manifestos (Gabel and Huber, 2000;Slapin and Proksch, 2008;Benoit et al, 2016). At the same time, politicians around the world increasingly use social media to communicate, and researchers are examining the impacts of that use on elections (Bossetta, 2018;Karlsen, 2011), the press (Murthy, 2015;Shapiro and Hemphill, 2017), and public opinion (Michael and Agur, 2018). Given its prevalence among politicians and in the public conversation about politics, politicians' behavior on Twitter deserves our attention.…”

mentioning

confidence: 99%

Two Computational Models for Analyzing Political Attention in Social Media

Hemphill

Schöpke‐Gonzalez

2020

ICWSM

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Understanding how political attention is divided and over what subjects is crucial for research on areas such as agenda setting, framing, and political rhetoric. Existing methods for measuring attention, such as manual labeling according to established codebooks, are expensive and can be restrictive. We describe two computational models that automatically distinguish topics in politicians' social media content. Our models—one supervised classifier and one unsupervised topic model—provide different benefits. The supervised classifier reduces the labor required to classify content according to pre-determined topic list. However, tweets do more than communicate policy positions. Our unsupervised model uncovers both political topics and other Twitter uses (e.g., constituent service). These models are effective, inexpensive computational tools for political communication and social media research. We demonstrate their utility and discuss the different analyses they afford by applying both models to the tweets posted by members of the 115th U.S. Congress.

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The Bully Pulpit, Social Media, and Public Opinion: A Big Data Approach

Cited by 7 publications

References 38 publications

Actors, Partisan Inclination, and Emotions: An Analysis of Government Shutdown News Stories Shared on Twitter

Actors, Partisan Inclination, and Emotions: An Analysis of Government Shutdown News Stories Shared on Twitter

The development and validation of the Indian social media addiction scale

Two Computational Models for Analyzing Political Attention in Social Media

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