Communication Methods and Measures最新文献

{"title":"Misclassification in Automated Content Analysis Causes Bias in Regression. Can We Fix It? Yes We Can!","authors":"Nathan TeBlunthuis, Valerie Hase, Chung-Hong Chan","doi":"10.1080/19312458.2023.2293713","DOIUrl":"https://doi.org/10.1080/19312458.2023.2293713","url":null,"abstract":"Automated classifiers (ACs), often built via supervised machine learning (SML), can categorize large, statistically powerful samples of data ranging from text to images and video. They have become ...","PeriodicalId":47552,"journal":{"name":"Communication Methods and Measures","volume":null,"pages":null},"PeriodicalIF":11.4,"publicationDate":"2024-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139489778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond sentiment: an algorithmic strategy for identifying evaluations within large text corpora","authors":"Maximilian Overbeck, Christian Baden, Tali Aharoni, Eedan Amit-Danhi, Keren Tenenboim-Weinblatt","doi":"10.1080/19312458.2023.2285783","DOIUrl":"https://doi.org/10.1080/19312458.2023.2285783","url":null,"abstract":"In this paper, we propose a new strategy for classifying evaluations in large text corpora, using supervised machine learning (SML). Departing from a conceptual and methodological critique of the u...","PeriodicalId":47552,"journal":{"name":"Communication Methods and Measures","volume":null,"pages":null},"PeriodicalIF":11.4,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138565235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Speaker landscapes: machine learning opens a window on the everyday language of opinion","authors":"Maria Schuld, Kevin Durrheim, Martin Mafunda","doi":"10.1080/19312458.2023.2277958","DOIUrl":"https://doi.org/10.1080/19312458.2023.2277958","url":null,"abstract":"We propose a new method that embeds speakers into a spatial representation according to the linguistic similarity of their contributions to a debate. Such “speaker landscapes” can be constructed qu...","PeriodicalId":47552,"journal":{"name":"Communication Methods and Measures","volume":null,"pages":null},"PeriodicalIF":11.4,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138559416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating Communication Science and Computational Methods to Study Content-Based Social Media Effects","authors":"J. Loes Pouwels, Theo Araujo, Wouter van Atteveldt, Marko Bachl, Patti M. Valkenburg","doi":"10.1080/19312458.2023.2285766","DOIUrl":"https://doi.org/10.1080/19312458.2023.2285766","url":null,"abstract":"A pressing societal and scientific question is how social media use affects our cognitions, emotions, and behaviors. To answer this question, fine-grained insight into the content of individuals’ s...","PeriodicalId":47552,"journal":{"name":"Communication Methods and Measures","volume":null,"pages":null},"PeriodicalIF":11.4,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138455127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Search for Solid Ground in Text as Data: A Systematic Review of Validation Practices and Practical Recommendations for Validation","authors":"Lukas Birkenmaier, Clemens M. Lechner, Claudia Wagner","doi":"10.1080/19312458.2023.2285765","DOIUrl":"https://doi.org/10.1080/19312458.2023.2285765","url":null,"abstract":"Communication research frequently applies computational text analysis methods (CTAM) to detect and measure social science constructs. However, the validity of these measures can be difficult to ass...","PeriodicalId":47552,"journal":{"name":"Communication Methods and Measures","volume":null,"pages":null},"PeriodicalIF":11.4,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138455094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated Visual Analysis for the Study of Social Media Effects: Opportunities, Approaches, and Challenges","authors":"Yilang Peng, Irina Lock, Albert Ali Salah","doi":"10.1080/19312458.2023.2277956","DOIUrl":"https://doi.org/10.1080/19312458.2023.2277956","url":null,"abstract":"To advance our understanding of social media effects, it is crucial to incorporate the increasingly prevalent visual media into our investigation. In this article, we discuss the theoretical opport...","PeriodicalId":47552,"journal":{"name":"Communication Methods and Measures","volume":null,"pages":null},"PeriodicalIF":11.4,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138297655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Acknowledgement","authors":"Denise Solomon","doi":"10.1080/19312458.2023.2276542","DOIUrl":"https://doi.org/10.1080/19312458.2023.2276542","url":null,"abstract":"Published in Communication Methods and Measures (Vol. 17, No. 4, 2023)","PeriodicalId":47552,"journal":{"name":"Communication Methods and Measures","volume":null,"pages":null},"PeriodicalIF":11.4,"publicationDate":"2023-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138293407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"WordPPR: A Researcher-Driven Computational Keyword Selection Method for Text Data Retrieval from Digital Media","authors":"Yini Zhang, Fan Chen, Jiyoun Suk, Zhiying Yue","doi":"10.1080/19312458.2023.2278177","DOIUrl":"https://doi.org/10.1080/19312458.2023.2278177","url":null,"abstract":"ABSTRACTDespite the increasing use of digital media data in communication research, a central challenge persists – retrieving data with maximal accuracy and coverage. Our investigation of keyword-based data collection practices in extant communication research reveals a one-step process, whereas our cross-disciplinary literature review suggests an iterative query expansion process guided by human knowledge and computer intelligence. Hence, we introduce the WordPPR method for keyword selection and text data retrieval, which entails four steps: 1) collecting an initial dataset using core/seed keyword(s); 2) constructing a word graph based on the dataset; 3) applying the Personalized PageRank (PPR) algorithm to rank words in proximity to the seed keyword(s) and selecting new keywords that optimize retrieval precision and recall; 4) repeating steps 1–3 to determine if additional data collection is needed. Without requiring corpus-wide sampling/analysis or extensive manual annotation, this method is well suited for data collection from large-scale digital media corpora. Our simulation studies demonstrate its robustness against parameter choice and its improvement upon other methods in suggesting additional keywords. Its application in Twitter data retrieval is also provided. By advancing a more systematic approach to text data retrieval, this study contributes to improving digital media data retrieval practices in communication research and beyond. AcknowledgementWe thank our reviewers, the editors, Dr. Karl Rohe, Dr. Nojin Kwak, and Dr. Dhavan Shah for their helpful feedback. We also thank Rui Wang, Dongdong Yang, and Xinxia Dong for assistance with the journal article coding.Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe method and application code files as well as the supplementary materials are available at https://osf.io/pcybz/.Supplementary materialSupplemental data for this article can be accessed online at https://doi.org/10.1080/19312458.2023.2278177.Additional informationNotes on contributorsYini ZhangYini Zhang (Ph.D., University of Wisconsin–Madison) is an assistant professor in the Department of Communication at the University at Buffalo, State University of New York. She studies social media, media ecosystem, and political communication, using computational methods.Fan ChenFan Chen (Ph.D., University of Wisconsin–Madison) is a Data Scientist at Google. He studies and develops statistical methods for social media, genomics, and advertisement data. The bulk of this work was completed while he was a Ph.D. student at the University of Wisconsin–Madison.Jiyoun SukJiyoun Suk (Ph.D., University of Wisconsin-Madison) is an assistant professor in the Department of Communication at the University of Connecticut. She studies the role of networked communication in shaping social trust, activism, and polarization, using computational methods.Zhiying YueZhiying Yue (Ph.D., University ","PeriodicalId":47552,"journal":{"name":"Communication Methods and Measures","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134991447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing Automated Content Analysis for a New Era of Media Effects Research: The Key Role of Transfer Learning","authors":"Anne Kroon, Kasper Welbers, Damian Trilling, Wouter van Atteveldt","doi":"10.1080/19312458.2023.2261372","DOIUrl":"https://doi.org/10.1080/19312458.2023.2261372","url":null,"abstract":"The availability of individual-level digital trace data offers exciting new ways to study media uses and effects based on the actual content that people encountered. In this article, we argue that ...","PeriodicalId":47552,"journal":{"name":"Communication Methods and Measures","volume":null,"pages":null},"PeriodicalIF":11.4,"publicationDate":"2023-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50164614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Linkage Analysis Revised – Linking Digital Traces and Survey Data","authors":"Lukas P. Otto, Felicia Loecherbach, Rens Vliegenthart","doi":"10.1080/19312458.2023.2257595","DOIUrl":"https://doi.org/10.1080/19312458.2023.2257595","url":null,"abstract":"Linkage analysis, i.e. linking media exposure, content, and surveys, has been a powerful tool to assess media effects. However, the development of online communication and the advent of social media brings about many challenges for traditional linkage designs. In this paper, we explain the three steps of linkage designs for online communication effects and the usage of computational approaches to capture communication exposure and content. We then review recent designs and studies that use different forms of digital trace data to link digital communication exposure, content, and surveys: Tracking data, data donations, and screenshots/screen recordings. We describe (practical) challenges and opportunities when linking digital communication traces with self-reports and show how these data could be analyzed to establish different media effects.","PeriodicalId":47552,"journal":{"name":"Communication Methods and Measures","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134911720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}