E-Participation, Decision Support Systems, Multi-document Natural Language Processing and Cognitive Bias Mitigation [via Collaborative Software Community Group]

Collaborative, productivity and e-participation software topics include those of
decision support systems and cognitive bias mitigation, including mitigating
cognitive biases pertaining to framing effects.

In a previous article, multi-document natural language processing technology
innovations were indicated including real-time fact checking, argument analysis,
spin and persuasion detection and sentiment analysis.

Multi-document natural language processing topics include:

1. Performing fact-checking upon collections of documents generated by
e-participants in their interactions and processes and upon external collections
of documents, the news, the arts and the Web

2. Performing argument analysis upon collections of documents generated by
e-participants in their interactions and processes and upon external collections
of documents, the news, the arts and the Web

3. Detecting spin and persuasion in collections of documents generated by
e-participants in their interactions and processes and in external collections
of documents, the news, the arts and the Web

4. Performing sentiment analysis upon collections of documents generated by
e-participants in their interactions and processes and upon external collections
of documents, the news, the arts and the Web

5. Detecting frame building and frame setting in collections of documents
generated by e-participants in their interactions and processes and in external
collections of documents, the news, the arts and the Web

6. Detecting agenda building and agenda setting in collections of documents
generated by e-participants in their interactions and processes and in external
collections of documents, the news, the arts and the Web

7. Detecting various sociolinguistic, social semiotic, sociocultural and memetic
events in collections of documents generated by e-participants in their
interactions and processes and in external collections of documents, the news,
the arts and the Web

8. Detecting the dynamics of the attention of individuals, groups and the
public

9. Detecting framing effects and other cognitive biases resulting from
simultaneous or proximate, parallel and sequential, discussions of topics and
subtopics

10. Presenting the detected real-time information to individuals and groups, the
users of e-participation venues; supporting situation awareness and sensemaking
from detected real-time information to individuals and groups, the users of
e-participation venues

Multi-document processing topics expand beyond processing natural language to
processing multimedia, for instance processing the images, photographs and
layouts in the e-participation documents, slide shows and presentations
generated, utilized and hyperlinked to by individuals and groups.

The topics pertain to the modeling of user contexts, to dialogue systems
technology, to digital personal assistants, digital group assistants, to
intelligent tutoring systems and to contextual or task-based information search
and retrieval technology.

The topics pertain to the planning of, the scheduling of and the automated
planning and scheduling of group tasks, activities and discussion topics. The
real-time information empowers individuals, team leaders, groups and
communities.

With 19,354 cities in the United States of America and city governments and
journalism organizations in nearly each, there is a market for services
described (points 1 to 10). Such service providers could access city resources,
including cloud-based, as well as third-party services, such as regional search
trends, to inform each individual participant and group, to ensure the quality
of e-participation venues, their real-time dashboards, their group discussions,
group reasoning and democratic processes.

See Also

Decision Support Systems, Cognitive Bias, Cognitive Bias Mitigation

Fact checker, Epistemology

Argumentation Theory, Theory of Justification

Spin, Persuasion, Manipulation, Media Manipulation

Sentiment Analysis

Framing, Framing Effect, Frame Building, Frame Setting

Agenda Building, Agenda Setting

Pragmatics, Situated Cognition, Frame Analysis, Sociolinguistics, Sociology of
Culture, Umwelten

Multitasking, Task Switching, Task Interference, Task Set, Mental Set,
Sensemaking, Situation Awareness, Mental Models

Group Cognition, Distributed Cognition, Social Cognition

Computational Journalism, Computer-assisted Reporting, Data-driven Journalism

References (Point 1)

Ciampaglia, Giovanni Luca, Prashant Shiralkar, Luis M. Rocha, Johan Bollen,
Filippo Menczer, and Alessandro Flammini. "Correction: Computational fact
checking from knowledge networks." PloS one 10, no. 10 (2015).

Cohen, Sarah, James T. Hamilton, and Fred Turner. "Computational journalism."
Communications of the ACM 54, no. 10 (2011): 66-71.

Goasdoué, François, Konstantinos Karanasos, Yannis Katsis, Julien Leblay,
Ioana Manolescu, and Stamatis Zampetakis. "Fact checking and analyzing the Web."
In Proceedings of the 2013 ACM SIGMOD International Conference on Management of
Data, pp. 997-1000. ACM, 2013.

Hassan, Naeemul, Bill Adair, James T. Hamilton, Chengkai Li, Mark Tremayne, Jun
Yang, and Cong Yu. "The quest to automate fact-checking." world (2015).

Pomares, Julia, and Noelia Guzmán. "Measuring the impact of fact-checking."

Walenz, Brett, You Will Wu, Seokhyun Alex Song, Emre Sonmez, Eric Wu, Kevin Wu,
Pankaj K. Agarwal et al. "Finding, monitoring, and checking claims
computationally based on structured data."

Wu, You, Pankaj K. Agarwal, Chengkai Li, Jun Yang, and Cong Yu. "Toward
computational fact-checking." Proceedings of the VLDB Endowment 7, no. 7 (2014):
589-600.

References (Point 2)

Boltuzic, Filip, and Jan Šnajder. "Back up your stance: Recognizing arguments
in online discussions." In Proceedings of the First Workshop on Argumentation
Mining, pp. 49-58. 2014.

Boltuzic, Filip, and Jan Šnajder. "Identifying Prominent Arguments in Online
Debates Using Semantic Textual Similarity."

Ghosh, Debanjan, Smaranda Muresan, Nina Wacholder, Mark Aakhus, and Matthew
Mitsui. "Analyzing argumentative discourse units in online interactions." In
Proceedings of the First Workshop on Argumentation Mining, pp. 39-48. 2014.

Goudas, Theodosis, Christos Louizos, Georgios Petasis, and Vangelis Karkaletsis.
"Argument extraction from news, blogs, and social media." In Artificial
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Publishing, 2014.

Lawrence, John, and Chris Reed. "Combining Argument Mining Techniques."

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propositions in online user comments." ACL 2014 (2014): 29.

Salah Z, Coenen F, Grossi D. Extracting debate graphs from parliamentary
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Sergeant, Alan. "Automatic argumentation extraction." In The semantic web:
Semantics and big data, pp. 656-660. Springer Berlin Heidelberg, 2013.

Sobhani, Parinaz, Diana Inkpen, and Stan Matwin. "From Argumentation Mining to
Stance Classification."

Swanson, Reid, Brian Ecker, and Marilyn Walker. "Argument Mining: Extracting
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References (Point 3)

Gilbert, Henry T. "Persuasion detection in conversation." PhD diss., Monterey,
California. Naval Postgraduate School, 2010.

Mills, Harry. Artful persuasion: How to command attention, change minds, and
influence people. AMACOM Div American Mgmt Assn, 2000.

Ortiz, Pedro. "Machine learning techniques for persuasion dectection in
conversation." PhD diss., Monterey, California. Naval Postgraduate School,
2010.

Stab, Christian, and Iryna Gurevych. "Identifying argumentative discourse
structures in persuasive essays." In Conference on Empirical Methods in Natural
Language Processing (EMNLP 2014)(Oct. 2014), Association for Computational
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Stab, Christian, and Iryna Gurevych. "Annotating argument components and
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Young, Joel, and Pedro Ortiz. "Automated Persuasion Detection in Conversation."
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References (Point 4)

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Liu B. Sentiment analysis and opinion mining. Synthesis Lectures on Human
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Liu B, Zhang L. A survey of opinion mining and sentiment analysis. In Mining
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Pang B, Lee L. Opinion mining and sentiment analysis. Foundations and trends in
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Sadegh M, Ibrahim R, Othman Z A. Opinion mining and sentiment analysis: A
survey. International Journal of Computers & Technology. 2012 Jun;2(3):171-8.

References (Point 5)

Borah, Porismita. "Conceptual issues in framing theory: A systematic examination
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Goffman, Erving. Frame analysis: An essay on the organization of experience.
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De Vreese, Claes H. "News framing: Theory and typology." Information design
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Hänggli, Regula. "Key factors in frame building: How strategic political actors
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Hänggli, Regula, and Hanspeter Kriesi. "Frame construction and frame promotion
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Matthes, Jörg, and Matthias Kohring. "The content analysis of media frames:
Toward improving reliability and validity." Journal of Communication 58, no. 2
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Matthes, Jörg. "What's in a frame? A content analysis of media framing studies
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Matthes, Jörg. "Framing politics: An integrative approach." American Behavioral
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Pan, Zhongdang, and Gerald M. Kosicki. "Framing as a strategic action in public
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Zhou, Yuqiong, and Patricia Moy. "Parsing framing processes: The interplay
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References (Point 6)

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References (Point 7)

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References (Point 8)

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References (Point 9)

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