Subject–method topic network analysis in communication studies

Lee, Keeheon; Jung, Hyojung; Song, Min

doi:10.1007/s11192-016-2135-7

Cited by 29 publications

(17 citation statements)

References 53 publications

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“…Similarly, Sinclair and Webber (2004) find that titles and abstracts yield classification analyses with the highest precision. Consistent with these findings, Chen et al ( 2020), Cretchley et al (2010), Lee et al (2016), Yan (2015) and Zhong et al (2016) conclude that abstracts are sufficient for capturing summaries of articles in terms of research aims and problems, as well as major findings. We thus conclude that the papers' abstract and introductory paragraphs will usually contain most (if not all) topic-related statements and words.…”

Section: Implementation Of the Lda Modelmentioning

confidence: 85%

Economists in the 2008 financial crisis: Slow to see, fast to act

Lévy

Mayer

Raviv

2022

Journal of Financial Stability

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Section: Implementation Of the Lda Modelmentioning

confidence: 85%

Economists in the 2008 financial crisis: Slow to see, fast to act

Lévy

Mayer

Raviv

2022

Journal of Financial Stability

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“…Communication studies typically try to understand human communication processes and include many subjects such as media studies, media law and ethics, the Internet, social media, broadcasting, mobile communication, political communication, personal communication, international communication, journalism, journalism trends and education, human-computer interaction, advertising, public relations, cultural studies, audience studies, and film studies (Calhoun, 2011;Lee, Jung, & Song, 2016). In recent years, online communication tools have created social spaces for professionals and social interactions.…”

Section: The Rise Of Big Data In Communication Studiesmentioning

confidence: 99%

“…Big data development in information and communication technology has shifted the attention of researchers from different disciplines to the field of communication and the big data-driven communication studies have rapidly started to gain great importance (e.g. Boyd, & Crawford, 2012;Lee, Jung, & Song, 2016;Lewis, Zamith, & Hermida, 2013;Manovich, 2011;Parks, 2017). Therefore, the number of articles in big data and communication studies has grown faster in the last decade and bibliometric analysis is considered to be the prominent way of reviewing related literature.…”

Section: Sampling and Data Collectionmentioning

confidence: 99%

The Rise of Big Data in Communication Sciences: A Bibliometric Mapping of the Literature

Karaboğa¹,

Şehitoğlu²

2020

CONNECTIST

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Today's digital world is characterized by advances in communication and information technologies. Internet technology provides a variety of communication channels like social media platforms, social network sites, search engines, blogs, forums, websites and e-mails. The users of these channels create digital traces which are the main source of big data in communication studies in social sciences. Big social data analytics in communication studies provides quantitative indicators to fully understand current situations rather than predefined cause and effect relationships. This study aims to investigate the studies in "big data and communication" in social sciences between the years 2014 and 2018. Web of Science Social Science Citation Index journals are selected to present systematic and quantitative analysis of the research field. Bibliometric analysis results provide insights about big data usage and expansion in the communication field not previously grasped by other reviews on this special topic. Bibliometric tools helped to identify research clusters, key research topics, and network and collaboration patterns in big data and communication studies in a social sciences context. This bibliometric mapping of the field visually illustrates the evolution of studies over time and identifies current research interests and future directions for the followers.

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“…Analyzing networks has many advantages, such as (a) moving beyond individual perception and thinking of individuals as embedded in groups to “varying degrees and thus differentially subject to the opportunities, constraints and influences created by group membership” (Marin & Wellman, 2011, p. 14), (b) defining the connectivity of groups and whether they are more cohesive or more permeable, and (c) exploring vague structures in social relations that are not clearly identifiable groups, such as weak ties or acquaintances (Freeman, 1978). Having access to these substantial advantages, SNA has been widely used to find the overall characteristics, internal construction, and core-periphery structure of networks (Himelboim, Smith, Rainie, Shneiderman, & Espina, 2017; K. Lee, Jung, & Song, 2016).…”

Section: Literature Reviewmentioning

confidence: 99%

The Rise of Fashion Informatics: A Case of Data-Mining-Based Social Network Analysis in Fashion

Zhao

Min

2018

Clothing and Textiles Research Journal

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With the advent of modern cognitive computing technologies, fashion informatics researchers contribute to the academic and professional discussion about how a large-scale data set is able to reshape the fashion industry. Data-mining-based social network analysis is a promising area of fashion informatics to investigate relations and information flow among fashion units. By adopting this pragmatic approach, we provide dynamic network visualizations of the case of Paris Fashion Week. Three time periods were researched to monitor the formulation and mobilization of social media users' discussions of the event. Initial textual data on social media were crawled, converted, calculated, and visualized by Python and Gephi. The most influential nodes (hashtags) that function as junctions and the distinct hashtag communities were identified and represented visually as graphs. The relations between the contextual clusters and the role of junctions in linking these clusters were investigated and interpreted.

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Subject–method topic network analysis in communication studies

Cited by 29 publications

References 53 publications

Economists in the 2008 financial crisis: Slow to see, fast to act

Economists in the 2008 financial crisis: Slow to see, fast to act

The Rise of Big Data in Communication Sciences: A Bibliometric Mapping of the Literature

The Rise of Fashion Informatics: A Case of Data-Mining-Based Social Network Analysis in Fashion

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