A novel search algorithm for quantifying news media coverage as a measure of environmental issue salience
News media plays an important role in shaping public opinions and attitudes about the environment. Tracking and analyzing media coverage can provide insight into public exposure to narratives that impact resource consumption, environmental behavior, and emergency response, which can help to inform m...
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| Published in | Environmental modelling & software : with environment data news Vol. 101; pp. 249 - 255 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Oxford
Elsevier Ltd
01.03.2018
Elsevier Science Ltd |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1364-8152 1873-6726 |
| DOI | 10.1016/j.envsoft.2017.12.012 |
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| Abstract | News media plays an important role in shaping public opinions and attitudes about the environment. Tracking and analyzing media coverage can provide insight into public exposure to narratives that impact resource consumption, environmental behavior, and emergency response, which can help to inform model development or provide additional model inputs. This paper presents Articulate, an open-source, flexible tool for discovering, compiling, and quantifying newspaper coverage on a user-specified topic. Articulate is written in Python and interfaces with Google Custom Search Engine API. We demonstrate the tool's application and validate its performance on two case studies of news media coverage in the New York Times about drought in California and flooding in Houston, Texas in recent years. Our results show that Articulate can generate data similar to or better than proprietary databases. Thus, Articulate can help researchers and environmental managers gain important insights to better understand and quantify changing socio-environmental dynamics.
•A Python package is developed for quantifying news media coverage of a topic of interest over a user-specified time period.•Our open-source tool performs like proprietary databases but with more flexible search customization and data manipulation.•Articulate provides insight into public exposure to environmental topics. |
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| AbstractList | News media plays an important role in shaping public opinions and attitudes about the environment. Tracking and analyzing media coverage can provide insight into public exposure to narratives that impact resource consumption, environmental behavior, and emergency response, which can help to inform model development or provide additional model inputs. This paper presents Articulate, an open-source, flexible tool for discovering, compiling, and quantifying newspaper coverage on a user-specified topic. Articulate is written in Python and interfaces with Google Custom Search Engine API. We demonstrate the tool's application and validate its performance on two case studies of news media coverage in the New York Times about drought in California and flooding in Houston, Texas in recent years. Our results show that Articulate can generate data similar to or better than proprietary databases. Thus, Articulate can help researchers and environmental managers gain important insights to better understand and quantify changing socio-environmental dynamics.
•A Python package is developed for quantifying news media coverage of a topic of interest over a user-specified time period.•Our open-source tool performs like proprietary databases but with more flexible search customization and data manipulation.•Articulate provides insight into public exposure to environmental topics. News media plays an important role in shaping public opinions and attitudes about the environment. Tracking and analyzing media coverage can provide insight into public exposure to narratives that impact resource consumption, environmental behavior, and emergency response, which can help to inform model development or provide additional model inputs. This paper presents Articulate, an open-source, flexible tool for discovering, compiling, and quantifying newspaper coverage on a user-specified topic. Articulate is written in Python and interfaces with Google Custom Search Engine API. We demonstrate the tool's application and validate its performance on two case studies of news media coverage in the New York Times about drought in California and flooding in Houston, Texas in recent years. Our results show that Articulate can generate data similar to or better than proprietary databases. Thus, Articulate can help researchers and environmental managers gain important insights to better understand and quantify changing socio-environmental dynamics. |
| Author | Roby, Nicholas A. Gonzales, Patricia Ajami, Newsha K. Quesnel, Kimberly J. |
| Author_xml | – sequence: 1 givenname: Nicholas A. surname: Roby fullname: Roby, Nicholas A. organization: Woods Institute for the Environment, 473 Via Ortega, Room 218B, Stanford University, Stanford, CA 94305, USA – sequence: 2 givenname: Patricia orcidid: 0000-0002-0956-8001 surname: Gonzales fullname: Gonzales, Patricia organization: ReNUWIt Engineering Research Center 473 Via Ortega, Room 117, Stanford University, Stanford, CA 94305, USA – sequence: 3 givenname: Kimberly J. orcidid: 0000-0002-4933-4218 surname: Quesnel fullname: Quesnel, Kimberly J. organization: ReNUWIt Engineering Research Center 473 Via Ortega, Room 117, Stanford University, Stanford, CA 94305, USA – sequence: 4 givenname: Newsha K. surname: Ajami fullname: Ajami, Newsha K. email: newsha@stanford.edu organization: Woods Institute for the Environment, 473 Via Ortega, Room 218B, Stanford University, Stanford, CA 94305, USA |
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| SubjectTerms | Algorithms California case studies computer software Data processing Drought Emergency preparedness Emergency response Environmental behavior Environmental impact Environmental management Flooding Google Custom Search Engine API information retrieval Interfaces Internet Media coverage News media News media coverage public opinion Python Resource consumption Search algorithms Search engines Search tool Source code Texas |
| Title | A novel search algorithm for quantifying news media coverage as a measure of environmental issue salience |
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