Social Science Computer Review

Research on the influence of digital technology on civic engagement debates whether Internet use leads to the decline of civic engagement or enables new social contacts and exchanges. We argue that whether Internet use has positive or negative effects on our civic engagement depends on how we use the Internet: Social Internet use and Internet use for information strengthen civic engagement, while private Internet use and Internet use for entertainment erode civic engagement. Data from the Longitudinal Internet Studies for the Social sciences (LISS) Panel and the Swiss Household Panel (SHP) allow us to employ differentiated measures of Internet use. In particular, their panel structure helps diminish the endogeneity problems of cross-sectional studies. By employing an autoregressive cross-lagged panel design, we are able to disentangle the relation between Internet use and associational participation and estimate the causal effect between the two variables in both directions. Analyzing associational participation as a pivotal pillar of the civil society, we show that social Internet use for information, in particular exchanging e-mails, but also being active on social network sites in the SHP, increases the likelihood of becoming or remaining active in an organization. At the same time, we fail to find consistent and robust evidence for the negative effects of Internet use. However, the causal relation also works the other way round: Associational participation was shown to increase the time respondents spend with writing e-mails, leading to a virtuous circle, whereby online and off-line forms of social engagement complement and enhance each other.

Virtual communities (VCs) have become essential in current organizations and society, and so their sustainability is a topic of interest for researchers and practitioners. We focus on the sense of virtual community (SoVC) and commitment as relevant antecedents in achieving the success and maintenance of different types of VCs (communities of interest, virtual learning communities, and VCs of practice). Specifically, this study examines a moderated mediation model in which the type of VC moderates the indirect effect of a SoVC on the intention to continue through the perceived commitment of the users of the VC. The sample consists of 299 members of VCs. The results showed that SoVC influenced the intention to continue via commitment to VCs. Additionally, the relationship between SoVC and commitment was higher for communities of interest and virtual learning communities than for VCs of practice. This article contributes to previous literature by identifying the importance of participants’ engagement and the contingent effect of the type of community. Implications of the study and directions for future research are discussed.

The present study examined the benefits of meeting new people on Facebook for social capital. Results of a two-wave national web survey (N = 387) indicate that using the site to meet and interact with new people relates to trusting more in the average person over time. Facebook sociability also moderates the negative association between neighborhood diversity and trust over time. Diversity has less of a negative impact on trust locally for users who interact with new people online. Novel interactions on sites like Facebook improve perceptions of difference, demonstrating value for reconnecting the populace.

This article distinguishes between clique family subgroups and communities in a crisis response network. Then, we examine the way organizations interacted to achieve a common goal by employing community analysis of an epidemic response network in Korea in 2015. The results indicate that the network split into two groups: core response communities in one group and supportive functional communities in the other. The core response communities include organizations across government jurisdictions, sectors, and geographic locations. Other communities are confined geographically, homogenous functionally, or both. We also find that whenever intergovernmental relations were present in communities, the member connectivity was low, even if intersectoral relations appeared together within them.

The trade in antiquities and cultural objects has proven difficult to understand and yet is highly dynamic. Currently, there are few computational tools that allow researchers to systematically understand the nature of the legal market, which can also potentially provide insights into the illegal market such as types of objects traded and countries trading antiquities. Online sales in antiquities and cultural objects are often unstructured data; relevant cultural affiliations, types, and materials for objects are important for distinguishing what might sell, but these data are rarely organized in a format that makes the quantification of sales a simple process. Additionally, sale locations and the total value of sales are relevant to understanding the focus and size of the market. These data all provide potentially useful insights into how the market in antiquities and cultural objects is developing. Based on this, this work presents the results of a machine learning approach using natural language processing and dictionary-based searches that investigate relatively low-end but high sales volume objects sold on eBay’s U.S. site, where sales are often international, between October 2018 and May 2019. The use of named entity recognition, using a conditional random field approach, classifies objects based on the cultures in which they come from, what type of objects they are, and what the objects are made of. The results indicate that objects from the United Kingdom, affiliated with the Roman period, mostly constituting jewelry, and made of metals sell the most. Metal and jewelry objects, in fact, sold more than other object types. Other important countries for selling ancient and cultural objects include the United States, Thailand, Germany, and Cyprus. Some countries appear to more greatly sellspecific types of objects, such as Egypt being a leader in selling Islamic, terracotta, stone, and wood artifacts and Germany selling Viking/early Medieval weapons. Overall, the approach and tool used demonstrate that it is possible to monitor the online antiquities and cultural objects market while potentially gaining useful insights into the market. The tool developed is provided as part of this work so that it can be applied for other cases and online sites, where it can be applied in real time or using historical data.

Altmetrics are a relatively new phenomenon in research. These metrics measure the attention that research articles receive from nontraditional venues such as social media and the Internet. This study examined how these metrics affect both the readership and citation of articles in communication research. The study examined citation data alongside altmetrics data from academic social networking sites ResearchGate and Mendeley, as well as mentions on Facebook, Twitter, and Google+. Results indicated that all altmetrics positively correlated with citation. Posting articles on sites such as ResearchGate and Mendeley not only impacted readership, it increased the likelihood of citation. Other variables that improved readership and citation were social media mentions, downloadable articles, coauthorship, and an active online presence among scholars.

Methodological studies usually gauge response quality in narrative open-ended questions with the proportion of nonresponse, response length, response time, and number of themes mentioned by respondents. However, not all of these indicators may be comparable and appropriate for evaluating open-ended questions in a cross-national context. This study assesses the cross-national appropriateness of these indicators and their potential bias. For the analysis, we use data from two web surveys conducted in May 2014 with 2,685 respondents and in June 2014 with 2,689 respondents and compare responses from Germany, Great Britain, the United States, Mexico, and Spain. We assess open-ended responses for a variety of topics (e.g., national identity, gender attitudes, and citizenship) with these indicators and evaluate whether they arrive at similar or contradictory conclusions about response quality. We find that all indicators are potentially biased in a cross-national context due to linguistic and cultural reasons and that the bias differs in prevalence across topics. Therefore, we recommend using multiple indicators as well as items covering a range of topics when evaluating response quality in open-ended questions across countries.

Cognitive online pretests have, in recent years, become recognized as a promising tool for evaluating questions prior to their use in actual surveys. While existing research has shown that cognitive online pretests produce similar results to face-to-face cognitive interviews with regard to the problems detected and the item revisions suggested, little is known about the ideal design of a cognitive online pretest. This study examines whether the number of open-ended probing questions asked during a cognitive online pretest has an effect on the quality and depth of respondents’ answers as well as on respondents’ satisfaction with the survey. We conducted an experiment in which we varied the number of open-ended probing questions that respondents received during a cognitive online pretest. The questionnaire consisted of 26 survey questions, and respondents received either 13 probing questions (n = 120, short version) or 21 probing questions (n = 120, long version). The findings suggest that asking a greater number of open-ended probes in a cognitive online pretest does not undermine the quality of respondents’ answers represented by the response quality indicators: (1) amount of probe nonresponse, (2) number of uninterpretable answers, (3) number of dropouts, (4) number of words, (5) response times, and (6) number and type of themes covered by the probes. Furthermore, the respondents’ satisfaction with the survey is not affected by the number of probes being asked.

Based on a sample of 21,546 individuals and 5,224 households, we use multilevel probit models to analyze the divides in the use of the Internet and online governmental services in Oman. We also study the main self-reported reasons for not using the Internet. The results reveal that characteristics such as education, employment status, nationality, role in the household, or age influence the likelihood of using both the Internet and online governmental services. Gender is only a relevant explanatory variable in the Internet use case. Although a gender divide exists in the online governmental services use, it is explained by differences in other individual characteristics. No need, lack of basic Information and Communication Technology skills and illiteracy are the most common explanations for not using the Internet.