A total of 39 articles, which reported cyberbullying behaviors from both male and female respondents, were meta-analyzed to examine if gender difference existed in cyberbullying perpetration. From these 39 empirical studies, a total of 100 effect sizes were collected, each representing a reported gender difference in certain types of cyberbullying behaviors. Random-effects meta-regression models were used in data analysis. Despite some inconsistencies across the individual empirical studies, a statistically significant gender difference emerged, indicating that more males were involved in cyberbullying perpetration behaviors than females. Moderator analysis showed that the gender difference was not consistent across the levels of several study features (e.g., modality of cyberbullying, regions of samples). It was also revealed that some methodological issues (e.g., measurement of cyberbullying behaviors, self-report rather than behavioral data) remain obvious challenges for researchers in this area. Caution is warranted, because those studies that were rated as having poor study quality showed a larger than average effect size for gender difference in cyberbullying behaviors. Implications and future research directions are discussed.
To compare two or more measures with regard to their internal consistency reliability, Cronbach’s alpha coefficients are usually computed for each measure. For a valid comparison between Cronbach’s alpha coefficients, substantive differences need to be distinguished from circumstantial differences that occur due to chance. Unfortunately, however, popular statistics packages lack the ability to test for statistically significant differences between alpha coefficients. To remedy this problem, we present cocron, a platform-independent R package that provides functions to conduct significance tests for the comparison of two or more Cronbach’s alpha coefficients for both dependent and independent groups of participants. The cocron package is part of the R statistical computing environment and is thus available for scripting. In addition, two graphical user interfaces – a web interface and a plugin for RKWard – are offered to provide comfortable access to the functionality of cocron.
We investigated using internet-based procedures to convert information from a large handwritten archive of ethnographic survey data into a computer addressable database. Rather than manually transcribing the archive's estimated 23,000 pages of handwritten data, we sought to develop novel crowdsourcing task designs, and to use an innovative variation of Cultural Consensus Analysis (CCT) to objectively aggregate crowdsourced responses based on a formal process model of shared knowledge. Experiment 1used simulated internet-based tasks conducted on human subject pool participants in a university laboratory. Experiment 2 used a similar design with the exception that it was implemented on an internet-based research platform (i.e., Amazon Mechanical Turk). Results from these investigations shed light on several uncertainties concerning the utility of CCT analyses with crowdsourced transcription data. For example, they clarify (1) whether crowdsourced tasks are practical as a method for automating the transcription of the archive's handwritten material, (2) whether responses from perceptually-based tasks inherent to transcribing handwritten documents can be analyzed using CCT, and (3) if CCT is appropriate as a model of the transcription challenge, then do the results produce accurate answer-key estimates that could serve as correct transcriptions of the archive's data. Our results address these issues and convey how CCT modeling can be modified and made appropriate for aggregating such data. Implications of these analyses and uses of CCT in large-scale crowdsourced data collection platforms are discussed.
The year 2016 has seen an unprecedented series of political campaigns that made use of the Internet, especially social media. Consequently, the Internet is increasingly being seen as a channel for influencing opinions, and it is being blamed for allowing spin doctors and other shady elements lurking at campaign trails in doing so without the necessity of content being related to facts. "Post-truth" was named the Oxford Dictionaries Word of the Year 2016, an adjective defined as "relating to or denoting circumstances in which objective facts are less influential in shaping public opinion than appeals to emotion and personal belief" (Oxford Dictionary, 2016). Relatedly, language institutions in several other languages followed suit, e.g. "postfaktisch" was also elected word of the year for German. The history of making new technologies responsible for societal developments beyond their actual impact is not new: when books were first printed, the invention of trains was thought to blind people, make them go crazy or cause female passengers' "uteruses ... fly out of [their] bodies" (Rooney, 2011). Old TV seems to get a break on its couch these days, while a crowd of teenage Internet services is being blamed for shattering the world's windows. In the current editorial, we take a close look at these "new Internet myths".
The current study focuses on the effect of the exclusion of non-Internet users in Web surveys. We raised the question whether it is worthwhile to invest in equipment to enable people without prior access to the Internet to participate in online surveys. To do so, we used data from the LISS panel in the Netherlands, which provides 'offliners' with equipment, called a SimPC. We investigate the differences between offliners (the SimPC group) and onliners (people with prior Internet access) in socio-demographics and answer scores for several questionnaires varying in theme. In addition, we look at associations between variables to investigate whether they are influenced by inclusion of the offliners. The results show that SimPC users differ significantly from the regular Internet users on most socio-demographic variables and on a variety of outcome variables in the studies in the panel. However, since the offline group is relatively small due to the high Internet penetration rate in the Netherlands, the inclusion of offliners does not cause any major differences compared to the Internet group alone. This suggests that it is not worthwhile to provide offline households with Internet access, unless one is particularly interested in doing subset analyses on the offline group. The size of the offline group in the panel is crucial. Not including offliners is ethically and scientifically problematic, however.
This article introduces the Conditional E-mail Response Technique (CERT) as a systematic, hidden observation technique to measure behavioral tendencies. Although CERT derives from older techniques such as lost-letter/lost-e-mail techniques, we show how CERT is unique: each participant receives several e-mails with varying content, allowing the researcher to observe response rates and valence as a function of the manipulated content. Our study investigated discrimination against foreigners in the apartment rental market in Heidelberg (a German university city) by recording lessors’ (non-) responses to 600 e-mails from fake applicants. Each owner (N = 120) received five applications for a one-room apartment via e-mail. Applicants’ ethnic identities were communicated through their names. The results showed a remarkable bias against foreign names compared to German names. The response rates for foreign applicants were almost half that for German applicants (response rates were 78% for German names compared to 44–54% for American, Italian, Russian, and Turkish names). The relative risk of a rejecting response was up to eight times higher for e-mails appearing to come from foreigners. Applicants with foreign names were noticeably more likely to receive either no response or a negative response, that is, to have a negative outcome. There were also differences among the foreign applicant groups. We discuss the implications, ethical considerations, and advantages of CERT compared to other related techniques, as well as possible future uses.
We examined whether the Big Five personality dimensions and choice of reimbursement ( participating in a lottery for a coupon vs. personality feedback) were related to respondents' motivation to continue filling out an online survey. A total of 3,013 individuals took part in an online study that asked them to rate a number of items separated into different question blocks. Using discrete-time survival analysis ( DTSA), we found that Openness, Agreeableness, Conscientiousness, and choosing to receive personality feedback had negative effects on dropout: They were related to a lower probability of quitting the survey. Furthermore, the effects of all four variables were mediated by satisfaction with the questionnaire in the previous question block. Practical implications for online research and implications regarding the role of personality in research participation in general are discussed.
With the advent of the internet, computer games have undergone substantial changes. Many games now contain some form of social interaction with other players. Furthermore, many games offer players the opportunity to buy upgrades using microtransactions. Based on social psychological theories on social comparisons, deservedness, and envy, we tested whether the use of these microtransactions would affect how players perceive another player using them. In one survey and two experimental scenario-studies with active gamers as participants (total N = 532), we found evidence supporting the idea that a player using microtransactions will be judged more negatively. More specifically, we find that gamers dislike it more when microtransactions allow the buying of functional benefits (that provide an in-game advantage) than when they are merely ornamental, and players who buy these functional benefits are respected less. In Studies 2 and 3 we found that players who use microtransactions are perceived as having a lower skill and status. This happens both when the microtransaction-using player is an enemy who bought a competitive advantage, as well as in games where one cooperates with the microtransaction-using player and the advantage is thus effectively shared. The findings have important practical implications for game-design. They indicate how micro-transactions can be implemented so that they have fewer negative social consequences, demonstrate the value of social psychological theories in predicting online behavior, and provide several avenues for further theoretical exploration. Keywords: Microtransactions, free-to-play, real money transactions, social comparisons, status, multiplayer gaming
Recent studies have shown that child abuse material is shared through peer-to-peer ( P2P) networks, which allow users to exchange files without a central server. Obtaining knowledge on the extent of this activity has major consequences for child protection, policy making and Internet regulation. Previous works have developed tools and analyses to provide overall figures in temporally-limited measurements. Offenders' behavior is mostly studied through small-scale interviews and there is few information on the times at which they engage in such activity. Here we show that the proportion of search-engine queries for pedophile content gradually has grown by a factor of almost 3 in three years. We also find that during the day, certain hours are, on average, privileged by seekers. Our results demonstrate that P2P networks are actively used to search for pedophile content and we find new and large-scale results on pedophile offenders' profile, indicating that a substantial proportion is well-integrated into family life and professional work activities.
Internet administration of established offline measures has become more and more common over the past years. Research has shown that online administration of a measure does not necessarily change its psychometric properties but one cannot simply assume that online versions of any measure are equivalent to offline counterparts. In a counterbalanced test-retest-design the web-enabled version of the Exchange Test was administered offline and online. Data were analyzed by means of repeated measurement ANOVA. Results indicated that both administration forms were parallel at the first measurement. Hence, online and offline administration seemed equivalent. However, data from the second measurement show they were not: Analyses revealed a main effect of repeated measurement and a systematic interaction of "repeated measurement" and "order of administration" (online-offline vs. offline-online). Comparable articles often report analyses based on one measurement only or aggregate data from repeated measurements. The present study shows by counterbalanced test-retest-design that there is the possibility of method effects that can only be detected in a cross-mode test-retest design and with appropriate analyses. Potential reasons for the significant differences between offline and online administration at the second measurement are discussed and theoretical explanation approaches are presented that may guide further research into the observed lack of equivalence.
Voting Advice Applications (VAAs) are Internet tools and a form of receptive political online communication that allow for a comparison of the individual's position on policy issues with those of parties and candidates running for election. Recently, these tools have experienced an increasing demand in Europe. However, a systematic approach to link the research on VAAs with research on political communication is missing. Therefore, the aim of this paper is to link these two research areas and to describe the users of the German VAA "Wahl-O-Mat" in more detail concerning their political communication patterns. Based on findings on the impact of the Internet for political communication and results from international VAA research hypotheses about the political communication habits of VAA users are formulated and tested by creating a political communication typology with a Latent Class Analysis (LCA). With this research strategy, we identify five classes with distinct political communication patterns among the online electorate by drawing on an online sample for the 2009 German Federal Election. The results show that even in the context of elections about half of the online population communicates only to a small extent about politics. Furthermore, using the Wahl-O-Mat is not an exclusive feature of an elite part of the Internet community, but the probability of using the Wahl-OMat increases with the bandwidth of political communication. Our analyses indicate that the tool reaches a heterogeneous share of people with regard to political communication, socio-demographic characteristics and political interest and overcomes patterns of political communication.
Using data from a large scale Annual Social Survey of the CBS in Israel, this study examines the first and second level digital divide between immigrants from the Former Soviet Union (FSU), Ethiopia, Western countries, and Jewish veterans in the Israeli society as manifested by Internet access and patterns of use. Western immigrants manifested the highest rates of Internet use, followed by native Israelis and FSU immigrants. The rate of Internet use among Ethiopian immigrants was significantly lower compared to the other three groups. After controlling for socio-economic variables and especially Hebrew proficiency, the gaps in Internet use between veteran Israelis and immigrants from the FSU and Ethiopia became insignificant. As for the second-level digital divide, among Internet users, the three immigrant groups closed the gap between them and veteran Israelis in human capital-enhancing forms of Internet use and manifested an advantage, compared to veterans, in social capital-enhancing forms of Internet use. Our important conclusion is that, background variables being the same, language proficiency explains ethnic differences in Internet usage as a whole and, more specifically, in human capital-enhancing Internet use. These findings are important for policy makers dealing with immigrant absorption, as they suggest that expansion of the variety of Hebrew learning courses according to immigrant level and specialization, for instance by combining Hebrew learning with the acquisition of digital literacy, might have beneficial effects.
This article introduces ReCal OIR, an extension to the existing ReCal suite of online intercoder reliability modules that accommodates ordinal, interval, and ratio levels of measurement. It includes a discussion of the currently available options for calculating reliability for the ordinal, interval, and ratio levels; explains what ReCal OIR does; validates its calculations; and discusses its usage data. The process of validating its output reveals ReCal OIR to be slightly more accurate than one of its major competitors.
Pro-social behavior, one of the defining characteristics of humans as social beings, plays a vital role in maintaining social bonds and in making social transactions possible. The questions which drive this study are whether there is any association between pro-social behavior or social capital online and offline, and whether we can see different patterns of effects of pro-social behavior on social capital online and offline. Using data obtained through an online survey of 1912 Internet users in Bosnia and Herzegovina, Croatia and Serbia, this study finds that pro-social behavior online and offline are closely related, as are social capital online and offline. In terms of the effects of pro-social behavior, however, we find that whereas online behavior has a stronger impact on online social capital than on offline social capital, the reverse does not hold: offline pro-social behavior has roughly the same impact on both types of social capital. Finally, online pro-social behavior is associated with a greater level of bridging offline social capital, suggesting positive spill-over effects from online acts of kindness. Our results inform future studies that wish to focus on pro-social behavior regarding the dual spheres in which it is present, as well as about the limited cross-over effects that exist between the two.
This cross-sectional study aimed to explore the association between the intensity of participation in online depression communities and the benefits users gain from participation. The study was based on an online survey of 631 users in 16 English language-based online depression communities. Results indicated that there were several differences between heavy, medium and light users with regard to their participation patterns, but they did not differ in their background characteristics and hardly varied in their interests. There were also no differences between the groups in their level of depression. However, there were many significant differences in perceived benefits gained, which demonstrated that heavy users reported receiving emotional support online and experiencing offline improvement more than medium and light users, and medium users reported these benefits more than light users. These findings suggest that contrary to some previous arguments regarding possible adverse consequences of intensive Internet use, heavy use of online depression communities is associated with positive results. Thus, it may even contribute to the general well-being of people with depression. Future research of the various associations between Internet use and psychological well-being should examine specific online activities, and explore diverse audiences including disadvantaged populations.
This paper investigates whether it is possible to improve the representativeness of an Internet panel by including non-Internet households. We study the LISS panel, managed by CentERdata, an Internet panel based on a probability sample that comprises approximately 5000 households. The LISS panel provides non-Internet households, households with no Internet access at the time of the sampling, with cost-free equipment and an Internet connection. Early 2010 the LISS panel contained 545 non-Internet households, this equals approximately 10% of the entire panel.The analyses show that particularly older households, non-western immigrants, and one-person households are less likely to have Internet access. The LISS panel includes a representative sample of non-Internet households except for households with high average age ("the oldest old"). Non-Internet households who participate in the panel show higher response rates on the individual questionnaires and lower attrition rates. While significant differences between the panel and the Dutch population remain, the complete LISS panel, with both Internet and non-Internet households, appears to be closer to the Dutch population than the panel consisting only of Internet households for all socio-demographic variables we tested. Furthermore, about half of the non-Internet households start to use the Internet after they have become panel members. They use less of the options offered by Internet, and mainly use the simpler applications, such as e-mail and information search, compared to persons living in Internet households. In this sense, they remain different from the original Internet households and continue to contribute to the quality of the panel data.
Three Web-based laboratory experiments explored the efficacy of three different Web-based tutorials designed to improve performance on Bayesian conditional probability estimation problems. In each experiment, participants estimated the probability of two events, and two conditional probabilities P(A|B) and P(B|A). Problems reflected five distinct relationships between two sets: identical sets, mutually exclusive sets, subsets, overlapping sets, and independent sets. Performance was measured against two benchmarks: internal inconsistency, a type of fallacy, and semantic coherence, a constellation of estimates of P(A), P(B), P(A|B), and P(B|A) that are consistent with the relationship among sets presented in the problem statement. As predicted by fuzzy-trace theory, in all three experiments, problems depicting identical sets, mutually exclusive sets, and independent sets yielded superior performance with respect to inconsistency and semantic coherence than problems depicting subsets and overlapping sets. In Experiment 1, a Web-based tutorial teaching the logic of the 2 ✕ 2 table reduced internal inconsistency for overlapping sets problems. In Experiment 2, a Web-based tutorial using Euler diagrams was effective in reducing inconsistency and increasing semantic coherence for overlapping sets and subsets problems. Experiment 3 employed AutoTutor Lite, the first Web-based Intelligent Tutoring System with two-way interactions with people in natural language (English). AutoTutor Lite is cross-platform enabled with talking animated agents that converse with learners using Latent Semantic Analysis to “understand” natural language. AutoTutor Lite elicits verbal responses from the learner through a textbox and encourages them to further elaborate their understanding. AutoTutor Lite tutorial significantly reduced internal inconsistency on overlapping sets and subsets problems.
The increasingly social nature of gaming suggests the importance of understanding its associated experiences and potential outcomes. This study examined the influence of social processes in gameplay and different gaming contexts on the experience of individual and group flow when engaged in the activity. It also examined the affective experiences associated with different types of social gaming. The research consisted of a series of focus groups with regular gamers. The results of the thematic analysis revealed the importance of social belonging, opportunities for social networking and the promotion of social integration for game enjoyment. However, social experiences could also facilitate feelings of frustration in gameplay as a result of poor social dynamics and competitiveness. The analysis also suggested that group flow occurs in social gaming contexts, particularly in cooperative gameplay. A number of antecedents of this shared experience were identified (e.g., collective competence, collaboration, task-relevant skills). Taken together, the findings suggest social gaming contexts enhance the emotional experiences of gaming. The study demonstrates the importance of examining social gaming processes and experiences to further understand their potential influence on associated affective outcomes. Areas of further empirical research are discussed in reference to the study's findings.
