Pub Date : 2022-02-01DOI: 10.5117/ccr2022.1.005.jurg
Pascal Jürgens, Christine E. Meltzer, Michael Scharkow
{"title":"Age and Gender Representation on German TV","authors":"Pascal Jürgens, Christine E. Meltzer, Michael Scharkow","doi":"10.5117/ccr2022.1.005.jurg","DOIUrl":"https://doi.org/10.5117/ccr2022.1.005.jurg","url":null,"abstract":"","PeriodicalId":275035,"journal":{"name":"Computational Communication Research","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121591873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-01DOI: 10.5117/ccr2022.1.001.joo
Jungseock Joo, Zachary C. Steinert-Threlkeld
Images matter because they help individuals evaluate policies, primarily through emotional resonance, and can help researchers from a variety of fields measure otherwise difficult to estimate quantities. The lack of scalable analytic methods, however, has prevented researchers from incorporating large scale image data in studies. This article offers an in-depth overview of automated methods for image analysis and explains their usage and implementation. It elaborates on how these methods and results can be validated and interpreted and discusses ethical concerns. Two examples then highlight approaches to systematically understanding visual presentations of political actors and events from large scale image datasets collected from social media. The first study examines gender and party differences in the self-presentation of the U.S. politicians through their Facebook photographs, using an off-the-shelf computer vision model, Google’s Label Detection API. The second study develops image classifiers based on convolutional neural networks to detect custom labels from images of protesters shared on Twitter to understand how protests are framed on social media. These analyses demonstrate advantages of computer vision and deep learning as a novel analytic tool that can expand the scope and size of traditional visual analysis to thousands of features and millions of images. The paper also provides comprehensive technical details and practices to help guide political communication scholars and practitioners.
{"title":"Image as Data: Automated Content Analysis for Visual Presentations of Political Actors and Events","authors":"Jungseock Joo, Zachary C. Steinert-Threlkeld","doi":"10.5117/ccr2022.1.001.joo","DOIUrl":"https://doi.org/10.5117/ccr2022.1.001.joo","url":null,"abstract":"Images matter because they help individuals evaluate policies, primarily through emotional resonance, and can help researchers from a variety of fields measure otherwise difficult to estimate quantities. The lack of scalable analytic methods, however, has prevented researchers from incorporating large scale image data in studies. This article offers an in-depth overview of automated methods for image analysis and explains their usage and implementation. It elaborates on how these methods and results can be validated and interpreted and discusses ethical concerns. Two examples then highlight approaches to systematically understanding visual presentations of political actors and events from large scale image datasets collected from social media. The first study examines gender and party differences in the self-presentation of the U.S. politicians through their Facebook photographs, using an off-the-shelf computer vision model, Google’s Label Detection API. The second study develops image classifiers based on convolutional neural networks to detect custom labels from images of protesters shared on Twitter to understand how protests are framed on social media. These analyses demonstrate advantages of computer vision and deep learning as a novel analytic tool that can expand the scope and size of traditional visual analysis to thousands of features and millions of images. The paper also provides comprehensive technical details and practices to help guide political communication scholars and practitioners.","PeriodicalId":275035,"journal":{"name":"Computational Communication Research","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132977269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-01DOI: 10.5117/ccr2022.1.007.neum
Mark W. Neumann, Erika Franklin Fowler, Travis N. Ridout
{"title":"Body Language and Gender Stereotypes in Campaign Video","authors":"Mark W. Neumann, Erika Franklin Fowler, Travis N. Ridout","doi":"10.5117/ccr2022.1.007.neum","DOIUrl":"https://doi.org/10.5117/ccr2022.1.007.neum","url":null,"abstract":"","PeriodicalId":275035,"journal":{"name":"Computational Communication Research","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116216234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-01DOI: 10.5117/ccr2022.1.003.chen
Kaiping Chen, Sang Jung Kim, Qiantong Gao, S. Raschka
{"title":"Visual Framing of Science Conspiracy Videos","authors":"Kaiping Chen, Sang Jung Kim, Qiantong Gao, S. Raschka","doi":"10.5117/ccr2022.1.003.chen","DOIUrl":"https://doi.org/10.5117/ccr2022.1.003.chen","url":null,"abstract":"","PeriodicalId":275035,"journal":{"name":"Computational Communication Research","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125567067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-01DOI: 10.5117/ccr2022.1.000.casa
Andreu Casas, N. Williams
{"title":"Introduction to the Special Issue on Images as Data","authors":"Andreu Casas, N. Williams","doi":"10.5117/ccr2022.1.000.casa","DOIUrl":"https://doi.org/10.5117/ccr2022.1.000.casa","url":null,"abstract":"","PeriodicalId":275035,"journal":{"name":"Computational Communication Research","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128956757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-01DOI: 10.5117/ccr2022.1.008.wu
P. Y. Wu, W. Mebane
{"title":"MARMOT","authors":"P. Y. Wu, W. Mebane","doi":"10.5117/ccr2022.1.008.wu","DOIUrl":"https://doi.org/10.5117/ccr2022.1.008.wu","url":null,"abstract":"","PeriodicalId":275035,"journal":{"name":"Computational Communication Research","volume":"06 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127229552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-01DOI: 10.5117/ccr2021.02.002.wald
A. Waldherr, Stephanie Geise, Merja Mahrt, Christian Katzenbach, Christian Nuernbergk
Computational communication science (CCS) is embraced by many as a fruitful methodological approach to studying communication in the digital era. However, theoretical advances have not been considered equally important in CCS. Specifically, we observe an emphasis on mid-range and micro theories that misses a larger discussion on how macro-theoretical frameworks can serve CCS scholarship. With this article, we aim to stimulate such a discussion. Although macro frameworks might not point directly to specific questions and hypotheses, they shape our research through influencing which kinds of questions we ask, which kinds of hypotheses we formulate, and which methods we find adequate and useful. We showcase how three selected theoretical frameworks might advance CCS scholarship in this way: (1) complexity theory, (2) theories of the public sphere, and (3) mediatization theory. Using online protest as an example, we discuss how the focus (and the blind spots) of our research designs shifts with each framework.
{"title":"Toward a Stronger Theoretical Grounding of Computational Communication Science","authors":"A. Waldherr, Stephanie Geise, Merja Mahrt, Christian Katzenbach, Christian Nuernbergk","doi":"10.5117/ccr2021.02.002.wald","DOIUrl":"https://doi.org/10.5117/ccr2021.02.002.wald","url":null,"abstract":"\u0000 Computational communication science (CCS) is embraced by many as a fruitful methodological approach to studying communication in the digital era. However, theoretical advances have not been considered equally important in CCS. Specifically, we observe an emphasis on mid-range and micro theories that misses a larger discussion on how macro-theoretical frameworks can serve CCS scholarship. With this article, we aim to stimulate such a discussion. Although macro frameworks might not point directly to specific questions and hypotheses, they shape our research through influencing which kinds of questions we ask, which kinds of hypotheses we formulate, and which methods we find adequate and useful. We showcase how three selected theoretical frameworks might advance CCS scholarship in this way: (1) complexity theory, (2) theories of the public sphere, and (3) mediatization theory. Using online protest as an example, we discuss how the focus (and the blind spots) of our research designs shifts with each framework.","PeriodicalId":275035,"journal":{"name":"Computational Communication Research","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114443770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-01DOI: 10.5117/ccr2021.3.001.lind
F. Lind, Tobias Heidenreich, Christoph Kralj, H. Boomgaarden
{"title":"Greasing the wheels for comparative communication research: Supervised text classification for multilingual corpora","authors":"F. Lind, Tobias Heidenreich, Christoph Kralj, H. Boomgaarden","doi":"10.5117/ccr2021.3.001.lind","DOIUrl":"https://doi.org/10.5117/ccr2021.3.001.lind","url":null,"abstract":"","PeriodicalId":275035,"journal":{"name":"Computational Communication Research","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125208579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Theo Araujo, J. Ausloos, Wouter van Atteveldt, Felicia Loecherbach, Judith Moeller, Jakob Ohme, D. Trilling, Bob van de Velde, Claes H. de Vreese, Kasper Welbers
The digital traces that people leave through their use of various online platforms provide tremendous opportunities for studying human behavior. However, the collection of these data is hampered by legal, ethical and technical challenges. We present a framework and tool for collecting these data through a data donation platform where consenting participants can securely submit their digital traces. This approach leverages recent developments in data rights that have given people more control over their own data, such as legislation that now mandates companies to make digital trace data available on request in a machine-readable format. By transparently requesting access to specific parts of this data for clearly communicated academic purposes, the data ownership and privacy of participants is respected and researchers are less dependent on commercial organizations that store this data in proprietary archives. In this paper we outline the general design principles, the current state of the tool, and future development goals.
{"title":"OSD2F: An Open-Source Data Donation Framework","authors":"Theo Araujo, J. Ausloos, Wouter van Atteveldt, Felicia Loecherbach, Judith Moeller, Jakob Ohme, D. Trilling, Bob van de Velde, Claes H. de Vreese, Kasper Welbers","doi":"10.31235/osf.io/xjk6t","DOIUrl":"https://doi.org/10.31235/osf.io/xjk6t","url":null,"abstract":"The digital traces that people leave through their use of various online platforms provide tremendous opportunities for studying human behavior. However, the collection of these data is hampered by legal, ethical and technical challenges. We present a framework and tool for collecting these data through a data donation platform where consenting participants can securely submit their digital traces. This approach leverages recent developments in data rights that have given people more control over their own data, such as legislation that now mandates companies to make digital trace data available on request in a machine-readable format. By transparently requesting access to specific parts of this data for clearly communicated academic purposes, the data ownership and privacy of participants is respected and researchers are less dependent on commercial organizations that store this data in proprietary archives. In this paper we outline the general design principles, the current state of the tool, and future development goals.","PeriodicalId":275035,"journal":{"name":"Computational Communication Research","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125909104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Austin Y. Hubner, Jessica McKnight, Matthew D. Sweitzer, Robert M. Bond
{"title":"Down to a r/science: Integrating Computational Approaches to the Study of Credibility on Reddit","authors":"Austin Y. Hubner, Jessica McKnight, Matthew D. Sweitzer, Robert M. Bond","doi":"10.17605/OSF.IO/UY85C","DOIUrl":"https://doi.org/10.17605/OSF.IO/UY85C","url":null,"abstract":"","PeriodicalId":275035,"journal":{"name":"Computational Communication Research","volume":"33 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114055171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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