Communication Methods and Measures最新文献_第5页

Digital Trace Data Collection for Social Media Effects Research: APIs, Data Donation, and (Screen) Tracking 社交媒体效果研究的数字跟踪数据收集:api，数据捐赠和(屏幕)跟踪

IF 11.4 1区文学

Communication Methods and Measures Pub Date : 2023-02-27 DOI: 10.1080/19312458.2023.2181319

Jakob Ohme, Theo Araujo, L. Boeschoten, Deen Freelon, Nilam Ram, Byron B. Reeves, Thomas N. Robinson

引用次数: 11

A Systematic Literature Review of Latent Variable Mixture Modeling in Communication Scholarship 传播学术中潜在变量混合模型的系统文献综述

IF 11.4 1区文学

Communication Methods and Measures Pub Date : 2023-02-23 DOI: 10.1080/19312458.2023.2179612

Colton E. Krawietz, Rudy C. Pett

{"title":"A Systematic Literature Review of Latent Variable Mixture Modeling in Communication Scholarship","authors":"Colton E. Krawietz, Rudy C. Pett","doi":"10.1080/19312458.2023.2179612","DOIUrl":"https://doi.org/10.1080/19312458.2023.2179612","url":null,"abstract":"ABSTRACT Recently, latent variable mixture modeling has gained traction in many disciplines, given its unique ability to discover unknown groups within a broader population. Indeed, this method assumes that a finite number of mixtures (i.e. unknown groups) exist within the population and can be discovered by evaluating participants’ response patterns to a set of manifest indicators. Despite the intuitive approach, recommendations have been proposed to overcome some methodological concerns associated with latent variable mixture modeling. The primary purpose of this study was to understand the characteristics of latent variable mixture modeling in communication research and to evaluate the extent to which the existing research meets these recommendations. Ninety-five manuscripts published between 2010 and 2022 in 18 communication journals were identified and systematically analyzed. The review found that (1) the use of latent variable mixture modeling has increased; (2) latent class analysis and latent profile analysis are the most common models; and (3) most manuscripts did not meet the proscribed standards for random start values, auxiliary variable procedures, indicator requirements, and missing data procedures. These findings are discussed more in comparison with the proscribed standards. In addition, conceptual and applicable recommendations are provided to improve communication scholarship.","PeriodicalId":47552,"journal":{"name":"Communication Methods and Measures","volume":"17 1","pages":"83 - 110"},"PeriodicalIF":11.4,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42567266","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

Correction 修正

IF 11.4 1区文学

Communication Methods and Measures Pub Date : 2023-02-23 DOI: 10.1080/19312458.2023.2182983

引用次数: 0

Leveraging Researcher Domain Expertise to Annotate Concepts Within Imbalanced Data 利用研究人员领域专业知识注释不平衡数据中的概念

IF 11.4 1区文学

Communication Methods and Measures Pub Date : 2023-02-22 DOI: 10.1080/19312458.2023.2182278

Dror K. Markus, Guy Mor-Lan, Tamir Sheafer, Shaul R. Shenhav

{"title":"Leveraging Researcher Domain Expertise to Annotate Concepts Within Imbalanced Data","authors":"Dror K. Markus, Guy Mor-Lan, Tamir Sheafer, Shaul R. Shenhav","doi":"10.1080/19312458.2023.2182278","DOIUrl":"https://doi.org/10.1080/19312458.2023.2182278","url":null,"abstract":"ABSTRACT As more computational communication researchers turn to supervised machine learning methods for text classification, we note the challenge in implementing such techniques within an imbalanced dataset. Such issues are critical in our domain, where, in many cases, researchers attempt to identify and study theoretically interesting categories that can be rare in a target corpus. Specifically, imbalanced distributions, with a skewed distribution of texts among the categories, can lead to a lengthy and expensive annotation stage, forcing practitioners to sample and label large numbers of texts to train a classification model. In this paper, we provide an overview of the issue, and describe existing strategies for mitigating such challenges. Noting the pitfalls of previous solutions, we then provide a semi-supervised method – Expert Initiated Latent Space Sampling – that complements researcher domain expertise with a systematic, unsupervised exploration of the latent semantic space to overcome such limitations. Utilizing simulations to systematically evaluate our method and compare it to existing approaches, we show that our procedure offers significant advantages in terms of efficiency and accuracy in many classification tasks.","PeriodicalId":47552,"journal":{"name":"Communication Methods and Measures","volume":"17 1","pages":"250 - 271"},"PeriodicalIF":11.4,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44019352","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

Developing an Incivility Dictionary for German Online Discussions – a Semi-Automated Approach Combining Human and Artificial Knowledge 为德语在线讨论开发一个不文明词典——一种结合人类和人工知识的半自动方法

IF 11.4 1区文学

Communication Methods and Measures Pub Date : 2023-02-05 DOI: 10.1080/19312458.2023.2166028

Anke Stoll, L. Wilms, Marc Ziegele

{"title":"Developing an Incivility Dictionary for German Online Discussions – a Semi-Automated Approach Combining Human and Artificial Knowledge","authors":"Anke Stoll, L. Wilms, Marc Ziegele","doi":"10.1080/19312458.2023.2166028","DOIUrl":"https://doi.org/10.1080/19312458.2023.2166028","url":null,"abstract":"ABSTRACT Incivility in online discussions has become an important issue in political communication research. Instruments and tools for the automated analysis of uncivil content, however, are rare, especially for non-English user-generated text. In this study, we present a) an extensive dictionary (DIKI - Diktionär für Inzivilität, English: Dictionary for Incivility) to detect incivility in German-language online discussions, and b) a semi-automated two-step-approach that combines manual content analysis with automated keyword collection using a pre-trained word embedding model. We show that DIKI clearly outperforms comparable dictionaries that have been used as alternative instruments to measure incivility (e.g., the LIWC) as well as basic machine learning approaches to text classification. Further, we provide evidence that pre-trained word embeddings can fruitfully be employed in the explorative phase of creating dictionaries. Still, the manual evaluation of DIKI confirms that detecting complex and context-dependent forms of incivility remains challenging and constant update would be needed to maintain performance. Finally, the detailed documentation of the developing and evaluation process of DIKI may serve as a guideline for further research. We therefore provide DIKI as a freely available instrument that also will be applicable in a web interface for drag-and-drop data analysis (diki.limitedminds.org).","PeriodicalId":47552,"journal":{"name":"Communication Methods and Measures","volume":"17 1","pages":"131 - 149"},"PeriodicalIF":11.4,"publicationDate":"2023-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43968197","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: 1

What We Can Do and Cannot Do with Topic Modeling: A Systematic Review 主题建模能做什么和不能做什么：系统综述

IF 11.4 1区文学

Communication Methods and Measures Pub Date : 2023-01-19 DOI: 10.1080/19312458.2023.2167965

Yingying Chen, Zhao Peng, Sei-Hill Kim, Chang Won Choi

引用次数: 9

Comparing Chatbots and Online Surveys for (Longitudinal) Data Collection: An Investigation of Response Characteristics, Data Quality, and User Evaluation 比较聊天机器人和在线调查的（纵向）数据收集：对响应特征、数据质量和用户评估的调查

IF 11.4 1区文学

Communication Methods and Measures Pub Date : 2023-01-12 DOI: 10.1080/19312458.2022.2156489

Brahim Zarouali, Theo Araujo, Jakob Ohme, Claes H. de Vreese

引用次数: 3

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