Network text analysis of conceptual overlap in interviews, newspaper articles and keywords

Martin, Michael K.; Carley, Kathleen M.

doi:10.1007/s13278-013-0129-5

Cited by 23 publications

(12 citation statements)

References 48 publications

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“…As described below, we pursued this goal by assessing trends in the prevalence of particular actors and issues, as well as in the network positions of these entities. These methods are based on a rapidly growing methodological tradition of computer-assisted text analysis (Brier & Hopp, 2010;Popping, 2000) and more specifically network text analysis (Carley, 1997;Martin, Pfeffer, & Carley, 2013).…”

Section: Methodsmentioning

confidence: 99%

Bill McKibben's Effect on the US Climate Change Debate: Shifting the Institutional Environment Through Radical Flank Effects

Schifeling

Hoffman

2017

SSRN Journal

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Section: Methodsmentioning

confidence: 99%

Bill McKibben's Effect on the US Climate Change Debate: Shifting the Institutional Environment Through Radical Flank Effects

Schifeling

Hoffman

2017

SSRN Journal

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“…Beyond classical metrics (Adamic and Glance 2005), networks have been shown to be efficient for topic and concept analysis (Martin et al 2013), and multiplex networks have been explored to analyse news data (Renoust et al 2014). In particular, character networks have been broadly analyzed from literature (Waumans et al 2015), from TV dramas (Nan et al 2015), and there is even a website dedicated to the social analysis of Game of Thrones (Mish 2015).…”

Section: Related Workmentioning

confidence: 99%

When face-tracking meets social networks: a story of politics in news videos

et al. 2016

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In the age of data processing, news videos are rich mines of information. After all, the news are essentially created to convey information to the public. But can we go beyond what is directly presented to us and see a wider picture? Many works already focus on what we can discover and understand from the analysis of years of news broadcasting. These analysis bring monitoring and understanding of the activity of public figures, political strategies, explanation and even prediction of critical media events. Such tools can help public figures in managing their public image, as well as support the work of journalists, social scientists and other media experts. News analysis can also be seen from the lens of complex systems, gathering many types of entities, attributes and interactions over time. As many public figures intervene in different news stories, a first interesting task is to observe the social interactions between these actors. Towards this goal, we propose to use video analysis to automatise the process of constructing social networks directly from news video archives. In this paper we are introducing a system deriving multiple social networks from face detections in news videos. We present preliminary results obtained from analysis of these networks, by monitoring the activity of more than a hundred public figures. We finally use these networks as a support for political studies and we provide an overview of the political landscape presented by the Japanese public broadcaster NHK over a decade of the 7 PM news archives.

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“…Later on, this approach has evolved into established and systematic research on structures of concept networks using dedicated software packages, like AutoMap and ORA, that are able to help automating the analysis of large sets of texts (e.g., Pfeffer and Carley, 2012;Diesner and Carley, 2005;Diesner, 2013;Martin, et al, 2013). This approach extends upon content analysis and requires human coding of the concepts.…”

Section: Semantic Networkmentioning

confidence: 99%

Integrating and differentiating meanings in tweeting about the fifth Intergovernmental Panel on Climate Change (IPCC) report

Holmberg

Hellsten

2016

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The publication of the fifth Intergovernmental Panel on Climate Change (IPCC) Working Group 1 report in September 2013 was highly debated on Twitter. In this paper we focused on tweets that mention "IPCC", and in particular the content and sentiment of the tweets sent by tweeters that were identified as unconvinced or as convinced towards the scientific basis of global warming. Our results indicate that the content and sentiment of those convinced reflect mainly information sharing activities instead of expressing opinions or participation in the debate. Climate change science is, however, challenged by some unconvinced tweeters who tend to use more negative words in their tweets. Our theoretical contribution is on the processes of meaning making around the IPCC report in relation to different groups of tweeters. We identify how certain words may be given different meanings by different groups, and how certain words have a differentiating function between the groups and integrating function within the groups. Our results increase our knowledge about the content of climate change debate in social media and on Twitter in particularly and contribute to research interested in how words function as differentiating and integrating meanings between and within social groups.

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Network text analysis of conceptual overlap in interviews, newspaper articles and keywords

Cited by 23 publications

References 48 publications

Bill McKibben's Effect on the US Climate Change Debate: Shifting the Institutional Environment Through Radical Flank Effects

Bill McKibben's Effect on the US Climate Change Debate: Shifting the Institutional Environment Through Radical Flank Effects

When face-tracking meets social networks: a story of politics in news videos

Integrating and differentiating meanings in tweeting about the fifth Intergovernmental Panel on Climate Change (IPCC) report

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