The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Discovering News Frames: An Approach for Exploring Text, Content, and Concepts in Online News Sources
|
|
Author(s): Loretta H. Cheeks (Arizona State University, Tempe, USA), Tracy L. Stepien (Arizona State University, Tempe, USA), Dara M. Wald (Iowa State University, Ames, USA)and Ashraf Gaffar (Arizona State University, Mesa, USA)
Copyright: 2020
Pages: 20
Source title:
Cognitive Analytics: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-2460-2.ch037
Purchase
|
Abstract
The Internet is a major source of online news content. Current efforts to evaluate online news content including text, storyline, and sources is limited by the use of small-scale manual techniques that are time consuming and dependent on human judgments. This article explores the use of machine learning algorithms and mathematical techniques for Internet-scale data mining and semantic discovery of news content that will enable researchers to mine, analyze, and visualize large-scale datasets. This research has the potential to inform the integration and application of data mining to address real-world socio-environmental issues, including water insecurity in the Southwestern United States. This paper establishes a formal definition of framing and proposes an approach for the discovery of distinct patterns that characterize prominent frames. The authors' experimental evaluation shows the proposed process is an effective approach for advancing semi-supervised machine learning and may assist in advancing tools for making sense of unstructured text.
Related Content
|
Jaime Salvador, Zoila Ruiz, Jose Garcia-Rodriguez.
© 2020.
12 pages.
|
|
Stavros Pitoglou.
© 2020.
11 pages.
|
|
Mette L. Baran.
© 2020.
13 pages.
|
|
Yingxu Wang, Victor Raskin, Julia M. Rayz, George Baciu, Aladdin Ayesh, Fumio Mizoguchi, Shusaku Tsumoto, Dilip Patel, Newton Howard.
© 2020.
15 pages.
|
|
Yingxu Wang, Lotfi A. Zadeh, Bernard Widrow, Newton Howard, Françoise Beaufays, George Baciu, D. Frank Hsu, Guiming Luo, Fumio Mizoguchi, Shushma Patel, Victor Raskin, Shusaku Tsumoto, Wei Wei, Du Zhang.
© 2020.
18 pages.
|
|
Nayem Rahman.
© 2020.
24 pages.
|
|
Amir Manzoor.
© 2020.
27 pages.
|
|
|