Discourse Analysis of Public Debates Using Corpus Linguistic Methodologies

Jeong, Heejin; Shiramatsu, Shun; Kobayashi, Kiyoshi; Hatori, Tsuyoshi

doi:10.4304/jcp.3.8.58-68

Cited by 14 publications

(12 citation statements)

References 18 publications

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“…propose a new methodology to investigate the level of discourse similarity and interest dissonance among participants in public debate objectively using first corpus of debate minutes. The level of discourse similarity and interest dissonance can be measured quantitatively by using discourse analysis of second corpus which is derived by Facet decomposition of first corpus [1], [2].…”

Section: The Basic Idea Of This Studymentioning

confidence: 99%

Analysis of public discussion in participatory planning process

Chosokabe

Sakakibara

Miyaji

et al. 2012

2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

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This study proposes the method of quantitative analysis on discussion in workshop for proper operation of discussion. It also shows the characteristics and the roles of discussion in workshop in planning process. There is a perception gap about policy issues of the region between planners who set up a workshop, and participants. The objectives of this study are to make clear its gap quantitatively, and to establish a management solution for minimizing them. This study provides quantitative analysis of a content of discussion to make participant's concern clear. The efficacy of this method is also discussed.

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Section: The Basic Idea Of This Studymentioning

confidence: 99%

Analysis of public discussion in participatory planning process

Chosokabe

Sakakibara

Miyaji

et al. 2012

2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

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“…In view of this, argument visualization is an effective approach for supporting eParticipation [9]. Jeong et al visualized the difference in cognition for several topics among participants in public debates using the co-occurrence of terms [10]. Visualizing an overview of public debate is also effective for grasping the background.…”

Section: B Modeling Public Debate and Participationmentioning

confidence: 99%

“…Figure 9 represents the processing flow for investigating the approximate examples. Firstly, we manually prepare the list of hashtags that may frequently cooccur with public concerns in Japanese tweets: # (politics), 10 . The ratio of public concern in this set is much less than that in the c …”

Section: Mining Feature Expression To Extract Concernsmentioning

confidence: 99%

SOCIA: Linked Open Data of Context behind Local Concerns for Supporting Public Participation

Shiramatsu¹,

Ozono²,

Shintani³

2015

ijacsa

Self Cite

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Abstract-To address public concerns that threat the sustainability of local societies, supporting public participation by sharing the background context behind these concerns is essentially important. We designed a SOCIA ontology, which was a linked data model, for sharing context behind local concerns with two approaches: (1) structuring Web news articles and microblogs about local concerns on the basis of geographical regions and events that were referred to by content, and (2) structuring public issues and their solutions as public goals. We moreover built a SOCIA dataset, which was a linked open dataset, on the basis of the SOCIA ontology. Web news articles and microblogs related to local concerns were semi-automatically gathered and structured. Public issues and goals were manually extracted from Web content related to revitalization from the Great East Japan Earthquake. Towards more accurate extraction of public concerns, we investigated feature expressions for extracting public concerns from microblogs written in Japanese. To address a technical issue about sample selection bias in our microblog corpus, we formulated a metric in mining feature expressions, i.e., bias-penalized information gain (BPIG). Furthermore, we developed a prototype of a public debate support system that utilized the SOCIA dataset and formulated the similarity between public goals for a goal matching service to facilitate collaboration.

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“…For example, Jeong et al (2007Jeong et al ( , 2008 proposed a methodology to investigate objectively the level of discourse similarity and interest dissonance among participants in public debates, by using discourse analysis based on corpus semantics. Chosokabe et al (2012) proposed a methodology based on text mining for conducting quantitative analysis of workshop discussions.…”

Section: Text Mining Approachmentioning

confidence: 99%

Dialogue Analysis Using a Text Mining Approach: Case Study of Hirono Town

Chosokabe

Sakamoto

Nakayama

2017

JAD

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This case study examined public participation regarding reconstruction of the disaster-affected areas in the Fukushima Prefecture of Japan following the Great East Japan Earthquake in March 2011. The study aimed at (i) identifying the topics discussed and shared by the residents, and (ii) revealing the contribution of the media to ensuring information transparency in the regional planning process. We applied text mining-in particular, correspondence analysis-to (a) the text data from dialogue sessions with local residents and (b) newspaper articles that appeared in a nation-wide newspaper in order to identify the similarities and differences between the topics discussed by session participants and those that appeared in newspaper articles. It turned out that the newspaper articles did not adequately address some important topics discussed in the dialogues. This implies that the coverage by the mass media has much room for improvement in the transparency of the information it provides and supporting the development and implementation of administrative agendas involving citizens and municipalities.

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Discourse Analysis of Public Debates Using Corpus Linguistic Methodologies

Cited by 14 publications

References 18 publications

Analysis of public discussion in participatory planning process

Analysis of public discussion in participatory planning process

SOCIA: Linked Open Data of Context behind Local Concerns for Supporting Public Participation

Dialogue Analysis Using a Text Mining Approach: Case Study of Hirono Town

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