Communication Methods and Measures最新文献_第5页

Conceptualizing and Examining Change in Communication Research. 对传播研究中的变化进行概念化和检验。

IF 6.3 1区文学

Communication Methods and Measures Pub Date : 2023-01-01 Epub Date: 2023-01-18 DOI: 10.1080/19312458.2023.2167197

Miriam Brinberg, David M Lydon-Staley

{"title":"Conceptualizing and Examining Change in Communication Research.","authors":"Miriam Brinberg, David M Lydon-Staley","doi":"10.1080/19312458.2023.2167197","DOIUrl":"10.1080/19312458.2023.2167197","url":null,"abstract":"Communication research often focuses on processes of communication, such as how messages impact individuals over time or how interpersonal relationships develop and change. Despite their importance, these change processes are often implicit in much theoretical and empirical work in communication. Intensive longitudinal data are becoming increasingly feasible to collect and, when coupled with appropriate analytic frameworks, enable researchers to better explore and articulate the types of change underlying communication processes. To facilitate the study of change processes, we (a) describe advances in data collection and analytic methods that allow researchers to articulate complex change processes of phenomena in communication research, (b) provide an overview of change processes and how they may be captured with intensive longitudinal methods, and (c) discuss considerations of capturing change when designing and implementing studies. We are excited about the future of studying processes of change in communication research, and we look forward to the iterations between empirical tests and theory revision that will occur as researchers delve into studying change within communication processes.","PeriodicalId":47552,"journal":{"name":"Communication Methods and Measures","volume":"17 1","pages":"59-82"},"PeriodicalIF":6.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10139745/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9404666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Investigating Opinions on Public Policies in Digital Media: Setting up a Supervised Machine Learning Tool for Stance Classification 调查数字媒体公共政策的意见:建立一个有监督的立场分类机器学习工具

IF 11.4 1区文学

Communication Methods and Measures Pub Date : 2022-12-12 DOI: 10.1080/19312458.2022.2151579

Christina Viehmann, Tilman Beck, Marcus Maurer, Oliver Quiring, Iryna Gurevych

{"title":"Investigating Opinions on Public Policies in Digital Media: Setting up a Supervised Machine Learning Tool for Stance Classification","authors":"Christina Viehmann, Tilman Beck, Marcus Maurer, Oliver Quiring, Iryna Gurevych","doi":"10.1080/19312458.2022.2151579","DOIUrl":"https://doi.org/10.1080/19312458.2022.2151579","url":null,"abstract":"ABSTRACT Supervised machine learning (SML) provides us with tools to efficiently scrutinize large corpora of communication texts. Yet, setting up such a tool involves plenty of decisions starting with the data needed for training, the selection of an algorithm, and the details of model training. We aim at establishing a firm link between communication research tasks and the corresponding state-of-the-art in natural language processing research by systematically comparing the performance of different automatic text analysis approaches. We do this for a challenging task – stance detection of opinions on policy measures to tackle the COVID-19 pandemic in Germany voiced on Twitter. Our results add evidence that pre-trained language models such as BERT outperform feature-based and other neural network approaches. Yet, the gains one can achieve differ greatly depending on the specific merits of pre-training (i.e., use of different language models). Adding to the robustness of our conclusions, we run a generalizability check with a different use case in terms of language and topic. Additionally, we illustrate how the amount and quality of training data affect model performance pointing to potential compensation effects. Based on our results, we derive important practical recommendations for setting up such SML tools to study communication texts.","PeriodicalId":47552,"journal":{"name":"Communication Methods and Measures","volume":"17 1","pages":"150 - 184"},"PeriodicalIF":11.4,"publicationDate":"2022-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46967481","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}

引用次数: 2

A New Scale for Measuring Identity Insecurity 一种新的身份不安全度量尺度

IF 11.4 1区文学

Communication Methods and Measures Pub Date : 2022-11-24 DOI: 10.1080/19312458.2022.2144631

Zachary B. Massey, Ioana A. Cionea

引用次数: 0

Lifting the Veil on the Use of Big Data News Repositories: A Documentation and Critical Discussion of A Protest Event Analysis 揭开大数据新闻库使用的面纱：抗议事件分析的文献和批判性讨论

IF 11.4 1区文学

Communication Methods and Measures Pub Date : 2022-09-28 DOI: 10.1080/19312458.2022.2128099

Matthias Hoffmann, Felipe G. Santos, Christina Neumayer, Dan Mercea

{"title":"Lifting the Veil on the Use of Big Data News Repositories: A Documentation and Critical Discussion of A Protest Event Analysis","authors":"Matthias Hoffmann, Felipe G. Santos, Christina Neumayer, Dan Mercea","doi":"10.1080/19312458.2022.2128099","DOIUrl":"https://doi.org/10.1080/19312458.2022.2128099","url":null,"abstract":"ABSTRACT This paper presents a critical discussion of the processing, reliability and implications of free big data repositories. We argue that big data is not only the starting point of scientific analyses but also the outcome of a long string of invisible or semi-visible tasks, often masked by the fetish of size that supposedly lends validity to big data. We unpack these notions by illustrating the process of extracting protest event data from the Global Database of Events, Language and Tone (GDELT) in six European countries over a period of seven years. To stand up to rigorous scientific scrutiny, we collected additional data by computational means and undertook large-scale neural-network translation tasks, dictionary-based content analyses, machine-learning classification tasks, and human coding. In a documentation and critical discussion of this process, we render visible opaque procedures that inevitably shape any dataset and show how this type of freely available datasets require significant additional resources of knowledge, labor, money, and computational power. We conclude that while these processes can ultimately yield more valid datasets, the supposedly free and ready-to-use big news data repositories should not be taken at face value.","PeriodicalId":47552,"journal":{"name":"Communication Methods and Measures","volume":"16 1","pages":"283 - 302"},"PeriodicalIF":11.4,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45060098","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}

引用次数: 4

Computer Vision and Internet Meme Genealogy: An Evaluation of Image Feature Matching as a Technique for Pattern Detection 计算机视觉与网络模因谱系:图像特征匹配作为模式检测技术的评价

IF 11.4 1区文学

Communication Methods and Measures Pub Date : 2022-09-22 DOI: 10.1080/19312458.2022.2122423

Cédric Courtois, Thomas Frissen

{"title":"Computer Vision and Internet Meme Genealogy: An Evaluation of Image Feature Matching as a Technique for Pattern Detection","authors":"Cédric Courtois, Thomas Frissen","doi":"10.1080/19312458.2022.2122423","DOIUrl":"https://doi.org/10.1080/19312458.2022.2122423","url":null,"abstract":"ABSTRACT Internet memes are a fundamental aspect of digital culture. Despite being individual expressions, they vastly transcend the individual level as windows into and vehicles for wide-stretching social, cultural, and political narratives. Empirical research into meme culture is thriving, yet particularly compartmentalized. In the humanities and social sciences, most efforts involve in-depth linguistic and visual analyses of mostly handpicked examples of memes, begging the question on the origins and meanings of those particular expressions. In technical disciplines, such as computer science, efforts are focused on the large-scale identification and classification of meme images, as well as patterns of “viral” spread at scale. This contribution aims to bridge the chasm between depth and scale by introducing a three-step approach suitable for “computational grounded theoretical” studies in which (1) an automated procedure establishes formal links between meme images drawn from a large-scale corpus paving the way for (2) network analysis to infer patterns of relatedness and spread, and (3) practically classifying visually related images in file folders for the purpose of further local, hermeneutic analysis. The procedure is demonstrated and evaluated on two datasets: an artificially constructed, structured dataset and a naturally harvested unstructured dataset. Future horizons and domains of application are discussed.","PeriodicalId":47552,"journal":{"name":"Communication Methods and Measures","volume":"17 1","pages":"17 - 39"},"PeriodicalIF":11.4,"publicationDate":"2022-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43629782","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}

引用次数: 0

Promises and Pitfalls of Social Media Data Donations 社交媒体数据捐赠的承诺和陷阱

IF 11.4 1区文学

Communication Methods and Measures Pub Date : 2022-09-12 DOI: 10.1080/19312458.2022.2109608

Irene I. van Driel, Anastasia Giachanou, J. Pouwels, L. Boeschoten, Ine Beyens, P. Valkenburg

引用次数: 11

Strong-Form Frequentist Testing In Communication Science: Principles, Opportunities, And Challenges 通信科学中的强形式频率测试:原理、机遇和挑战

IF 11.4 1区文学

Communication Methods and Measures Pub Date : 2022-09-09 DOI: 10.1080/19312458.2022.2086690

L. Coenen, T. Smits

引用次数: 1

Metrics of News Audience Polarization: Same or Different? 新闻受众两极分化的度量:相同还是不同?

IF 11.4 1区文学

Communication Methods and Measures Pub Date : 2022-07-03 DOI: 10.1080/19312458.2022.2085249

F. Mangold, Michael Scharkow

引用次数: 1

An Empirical Investigation of Inadequate Statistical Reporting Practices in Communication Meta-Analyses and Their Consequences 沟通元分析中统计报告实践不足及其后果的实证研究

IF 11.4 1区文学

Communication Methods and Measures Pub Date : 2022-06-27 DOI: 10.1080/19312458.2022.2088713

Stephanie K Van Stee, Qinghua Yang, Stephen A. Rains

引用次数: 0

Correcting Sample Selection Bias of Historical Digital Trace Data: Inverse Probability Weighting (IPW) and Type II Tobit Model 修正历史数字轨迹数据的样本选择偏差：逆概率加权（IPW）和II型Tobit模型

IF 11.4 1区文学

Communication Methods and Measures Pub Date : 2022-02-18 DOI: 10.1080/19312458.2022.2037537

Chankyung Pak, Kelley Cotter, Kjerstin Thorson

引用次数: 0