{"title":"Not All Bots are Created Equal: The Impact of Bots Classification Techniques on Identification of Discursive Behaviors Around the COVID-19 Vaccine and Climate Change","authors":"Rui Wang, Dror Walter, Y. Ophir","doi":"10.1177/08944393231188472","DOIUrl":"https://doi.org/10.1177/08944393231188472","url":null,"abstract":"As concerns about social bots online increase, studies have attempted to explore the discourse they produce, and its effects on individuals and the public at large. We argue that the common reliance on aggregated scores of binary classifiers for bot detection may have yielded biased or inaccurate results. To test this possibility, we systematically compare the differences between non-bots and bots using binary and non-binary classifiers (classified into the categories of astroturf, self-declared, spammers, fake followers, and Other). We use two Twitter corpora, about COVID-19 vaccines ( N = 1,697,280) and climate change ( N = 1,062,522). We find that both in terms of volume and thematic content, the use of binary classifiers may hinder, distort, or mask differences between humans and bots, that could only be discerned when observing specific bot types. We discuss the theoretical and practical implications of these findings.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":" ","pages":""},"PeriodicalIF":4.1,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42125594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Leona Yi-Fan Su, Tianli Chen, Yee Man Margaret Ng, Ziyang Gong, Yi-Cheng Wang
{"title":"Integrating Human Insights Into Text Analysis: Semi-Supervised Topic Modeling of Emerging Food-Technology Businesses’ Brand Communication on Social Media","authors":"Leona Yi-Fan Su, Tianli Chen, Yee Man Margaret Ng, Ziyang Gong, Yi-Cheng Wang","doi":"10.1177/08944393231184532","DOIUrl":"https://doi.org/10.1177/08944393231184532","url":null,"abstract":"Textual social media data have become indispensable to researchers’ understanding of message strategies and other marketing practices. In a new departure for the field of brand communication, this study adopts and extends a semi-supervised machine-learning approach, guided latent Dirichlet allocation (LDA), which incorporates human insights into the discovery and classification of topics. We used it to analyze tweets from businesses involved with an emerging food technology, cultured meat, and delineated four key message strategies used by these brands: providing functional, educational, corporate social responsibility, and relational content. We further ascertained the relationships between brands and the key topics embedded in their Twitter data. A comparison of model performance suggests that guided LDA can be an advantageous alternative to traditional LDA, which is characterized by high efficiency and immense popularity among researchers, but—because of its unsupervised nature—yields findings that can be difficult to interpret. The present study therefore has critical theoretical and methodological implications for communication and marketing scholars.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":" ","pages":""},"PeriodicalIF":4.1,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48475078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhan Xu, Veronica U. Weser, Luluo Peng, Mary Laffidy
{"title":"Incorporating Virtual Reality in Public Health Campaigns: COVID-19 as the Context","authors":"Zhan Xu, Veronica U. Weser, Luluo Peng, Mary Laffidy","doi":"10.1177/08944393231185257","DOIUrl":"https://doi.org/10.1177/08944393231185257","url":null,"abstract":"One of the greatest challenges for public health campaigns is communicating health risks due to the existence of psychological distance. Using COVID-19 as a context, this study designed and tested virtual reality (VR) campaigns based on construal level theory. It assessed the immediate and after-effects of VR on COVID-19 preventive intentions/behaviors and risk perceptions. A total of 120 participants were randomly assigned to see one of four messages: a VR message emphasizing self-interest, a VR message emphasizing other-interest, a print message emphasizing self-interest, or a print message emphasizing other-interest. Preventive intentions/behaviors were assessed at three different times: before, immediately after, and one week after the experimental treatment. Immediately following message exposure, participants exposed to the VR messages perceived a higher level of self-risk than those exposed to print messages. Disgust and fear mediated these effects. One week following message exposure, unvaccinated participants exposed to the VR messages had a higher intention to get vaccinated than those exposed to print messages. Recommendations on how to effectively utilize VR in health interventions are provided.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":" ","pages":""},"PeriodicalIF":4.1,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49304160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Dynamic Analysis of the Timing of Survey Participation: An Application of Event History Analysis of the Stochastic Process of Response in a Probability-Based Multi-Wave Panel With Computer-Assisted Interview Modes","authors":"R. Becker","doi":"10.1177/08944393231183871","DOIUrl":"https://doi.org/10.1177/08944393231183871","url":null,"abstract":"The response patterns across the fieldwork period are analyzed in the context of a panel study with a sequential mixed-mode design including a self-administered online questionnaire and a computer-assisted telephone interview. Since the timing of participation is modelled as a stochastic process of individuals’ response behaviour, event history analysis is applied to reveal time-constant and time-varying factors that influence this process. Different distributions of panelists’ propensity for taking part in the web-based survey or, alternatively, in the computer-assisted telephone interview can be considered by hazard rate analysis. Piecewise constant rate models and analysis of sub-episodes demonstrate that it is possible to describe the time-related development of response rates by reference to individuals’ characteristics, resources and abilities, as well as panelists’ experience with previous panel waves. Finally, it is shown that exogenous factors, such as a mixed-mode survey design, the incentives offered to participants and the reminders that are sent out, contribute significantly to time-related response after the invitation to participate in a survey with a sequential mixed-mode design. Overall, this contribution calls for a dynamic analysis of response behaviour instead of the categorization of response groups.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":" ","pages":""},"PeriodicalIF":4.1,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48816323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Emoji as a Social Presence Tool Among Arab Digital Media Users: Do the Demographic Variables of the Sender Play a Role?","authors":"Shuaa Aljasir","doi":"10.1177/08944393231181638","DOIUrl":"https://doi.org/10.1177/08944393231181638","url":null,"abstract":"To contribute to the current knowledge, this research was conducted, perhaps for the first time, among 1354 Arab users of digital media platforms to investigate emoji as a social presence tool and how the variables of the gender, generation, and the sender’s relationship to the receiver affect the usage and interpretation of the appropriateness of these graphical icons. Among the significant results of this study, generation and gender explained a significant amount of the variance in the frequency and motivation index. Interestingly, there was a significant, three-way interaction among senders’ gender, raters’ gender, and salience. The analysis also showed that the generation and relationship of the sender had a statistically significant effect on appropriateness ratings.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":" ","pages":""},"PeriodicalIF":4.1,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48928846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Standby Ties that Mobilize: Social Media Platforms and Civic Engagement.","authors":"Shelley Boulianne","doi":"10.1177/08944393211067687","DOIUrl":"https://doi.org/10.1177/08944393211067687","url":null,"abstract":"<p><p>Nonprofit organizations and groups depend on donations and volunteers for their survival. Digital media can help by offering a platform for making online donations and facilitating online volunteering, but also by identifying and connecting with people who are sympathetic to an organization's mission. This article employs four-country (USA, UK, France, and Canada) representative survey data (<i>n</i> = 6291) to examine the use of social media for establishing connections between citizens and organizations as well as the relationship of these connections to online and offline volunteering and donating. Across all social media platforms considered (Facebook, Instagram, and Twitter), I find significant positive correlations of following nonprofits with online and offline volunteering and donating. However, Facebook has a slightly larger role, which may be attributed to its overall popularity, which can incentivize organizations' more intense use of this platform.</p>","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"41 3","pages":"1001-1016"},"PeriodicalIF":4.1,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10240620/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10297966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Arne Weigold, Ingrid K. Weigold, Xiangling Zhang, Ning Tang, Yun Kai Chong
{"title":"Translation and Validation of the Brief Inventory of Technology Self-Efficacy (BITS): Simplified and Traditional Chinese Versions","authors":"Arne Weigold, Ingrid K. Weigold, Xiangling Zhang, Ning Tang, Yun Kai Chong","doi":"10.1177/08944393231176596","DOIUrl":"https://doi.org/10.1177/08944393231176596","url":null,"abstract":"Computer self-efficacy (CSE) continues to be an important construct in research and application. Two measures of CSE, the Brief Inventory of Technology Self-Efficacy (BITS) and the Brief Inventory of Technology Self-Efficacy – Short Form (BITS-SF) were recently developed to correct for issues in other available measures. The BITS and BITS-SF were originally written in English, and their psychometric properties assessed in samples from the United States. The current two studies translated the BITS and BITS-SF into simplified Chinese (Mainland China) and traditional Chinese (Taiwan) and assessed their psychometric properties. In Study 1, 207 adults in Mainland China completed the simplified Chinese BITS and BITS-SF, as well as measures given to assess convergent, discriminant, and concurrent validity. In Study 2, 273 adults in Taiwan did the same, except that they completed the traditional Chinese BITS and BITS-SF. In both studies, the translated BITS showed evidence of a three-factor correlated structure, and the translated BITS-SF yielded several underlying classes consistent with theory and scoring interpretation. Additionally, the translated measures’ scores showed solid evidence of convergent, discriminant, and concurrent validity. The results replicate the findings using the original BITS and BITS-SF and extend them to simplified Chinese and traditional Chinese translated versions. These versions are recommended for use in research and applied settings to assess CSE and are available for use. Both the original and translated measures are available for download at www.bitssurvey.com .","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135642771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Seeded Sequential LDA: A Semi-Supervised Algorithm for Topic-Specific Analysis of Sentences","authors":"Kohei Watanabe, A. Baturo","doi":"10.1177/08944393231178605","DOIUrl":"https://doi.org/10.1177/08944393231178605","url":null,"abstract":"Topic models have been widely used by researchers across disciplines to automatically analyze large textual data. However, they often fail to automate content analysis, because the algorithms cannot accurately classify individual sentences into pre-defined topics. Aiming to make topic classification more theoretically grounded and content analysis in general more topic-specific, we have developed Seeded Sequential Latent Dirichlet allocation (LDA), extending the existing LDA algorithm, and implementing it in a widely accessible open-source package. Taking a large corpus of speeches delivered by delegates at the United Nations General Assembly as an example, we explain how our algorithm differs from the original algorithm; why it can classify sentences more accurately; how it accepts pre-defined topics in deductive or semi-deductive analysis; how such ex-ante topic mapping differs from ex-post topic mapping; how it enables topic-specific framing analysis in applied research. We also offer practical guidance on how to determine the optimal number of topics and select seed words for the algorithm.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":" ","pages":""},"PeriodicalIF":4.1,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49102713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Impact of day of Mailing on Web Survey Response Rate and Response Speed","authors":"Peter Lynn, A. Bianchi, A. Gaia","doi":"10.1177/08944393231173887","DOIUrl":"https://doi.org/10.1177/08944393231173887","url":null,"abstract":"The day of the week on which sample members are invited to participate in a web survey might influence propensity to respond, or to respond promptly (within two days from the invitation). This effect could differ between sample members with different characteristics. We explore such effects using a large-scale experiment implemented on the Understanding Society Innovation Panel, in which some people received an invitation on a Monday and some on a Friday. Specifically, we test whether any effect of the invitation day is moderated by economic activity status (which may result in a different organisation of time by day of the week), previous participation in the panel, or whether the invitation was sent only by post or by post and email simultaneously. Overall, we do not find any effect of day of invitation in survey participation or in prompt participation. However, sample members who provided an email address, and, thus, were contacted by email in addition to postal letter, are less likely to participate if invited on Friday (email reminders: Sunday and Tuesday) as opposed to Monday (email reminders: Wednesday and Friday). Given that no difference between the two protocols is found for prompt response, the effect seems to be due to the day of mailing of reminders. With respect to sample members' economic activity status, those not having a job and the retired are less likely to participate when invited on a Friday; this result holds also for prompt participation, but only for retired respondents. Also, sample members who work long hours are less likely to participate when invited on a Friday; however, no effect is found for prompt response.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":" ","pages":""},"PeriodicalIF":4.1,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46306503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Integrating Street Views, Satellite Imageries and Remote Sensing Data Into Economics and the Social Sciences","authors":"Guan Wang","doi":"10.1177/08944393231178604","DOIUrl":"https://doi.org/10.1177/08944393231178604","url":null,"abstract":"Street views, satellite imageries and remote sensing data have been integrated into a wide spectrum of topics in the social sciences. Computer vision methods not only help analysts and policymakers make better decisions and produce more effective solutions but they also enable models to achieve more precise predictions and greater interpretability. In this paper, we review the growing literature applying such methods to economic issues and the social sciences, in which social scientists employ deep learning approaches to utilise image data to retrieve additional information. Typically, image data produce better results than traditional approaches and can provide detailed results and helpful insights to improve society and people’s well-being.","PeriodicalId":49509,"journal":{"name":"Social Science Computer Review","volume":" ","pages":""},"PeriodicalIF":4.1,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42886068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}