Data-driven Computational Social Science: A Survey

Social science concerns issues on individuals, relationships, and the whole society. The complexity of research topics in social science makes it the amalgamation of multiple disciplines, such as economics, political science, and sociology, etc. For centuries, scientists have conducted many studies to understand the mechanisms of the society. However, due to the limitations of traditional research methods, there exist many critical social issues to be explored. To solve those issues, computational social science emerges due to the rapid advancements of computation technologies and the profound studies on social science. With the aids of the advanced research techniques, various kinds of data from diverse areas can be acquired nowadays, and they can help us look into social problems with a new eye. As a result, utilizing various data to reveal issues derived from computational social science area has attracted more and more attentions. In this paper, to the best of our knowledge, we present a survey on data-driven computational social science for the first time which primarily focuses on reviewing application domains involving human dynamics. The state-of-the-art research on human dynamics is reviewed from three aspects: individuals, relationships, and collectives. Specifically, the research methodologies used to address research challenges in aforementioned application domains are summarized. In addition, some important open challenges with respect to both emerging research topics and research methods are discussed.Comment: 28 pages, 8 figure

Predicting self‐declared movie watching behavior using Facebook data and information‐fusion sensitivity analysis

The main purpose of this paper is to evaluate the feasibility of predicting whether yes or no a Facebook user has self-reported to have watched a given movie genre. Therefore, we apply a data analytical framework that (1) builds and evaluates several predictive models explaining self-declared movie watching behavior, and (2) provides insight into the importance of the predictors and their relationship with self-reported movie watching behavior. For the first outcome, we benchmark several algorithms (logistic regression, random forest, adaptive boosting, rotation forest, and naive Bayes) and evaluate their performance using the area under the receiver operating characteristic curve. For the second outcome, we evaluate variable importance and build partial dependence plots using information-fusion sensitivity analysis for different movie genres. To gather the data, we developed a custom native Facebook app. We resampled our dataset to make it representative of the general Facebook population with respect to age and gender. The results indicate that adaptive boosting outperforms all other algorithms. Time- and frequency-based variables related to media (movies, videos, and music) consumption constitute the list of top variables. To the best of our knowledge, this study is the first to fit predictive models of self-reported movie watching behavior and provide insights into the relationships that govern these models. Our models can be used as a decision tool for movie producers to target potential movie-watchers and market their movies more efficiently

An exploratory investigation on the effects of online social networking sites on college students

The purpose of this study was to examine the effects online social networking sites have on college students, mainly the effects on their communication. A study at Rowan University was conducted using a random selection of undergraduate students. The Rowan Subject pool was used to recruit students. Although each student was in different majors, all of the students were in an introduction to psychology course. To examine the effects online social networking sites have on college students, there were two separate groups of students designed to interact with one another in two different ways. A group was instructed to communicate face-to-face on a topic and the group were audio and visually recorded. The other group was instructed to communicate through a Facebook page created by the researcher. A status was posted on the main page and the subjects were instructed to communication via Facebook. To examine communication, the number of words was counted. I hypothesized due to the increased use of online social networking sites; the group communicating through Facebook would have a higher word count than the group communicating face-to-face

Student-Instructor Out-of-Class Communication: A Media Multiplexity Approach

The present set of studies examined media multiplexity theory (MMT; Haythornthwaite, 2005) in the context of student-instructor out-of-class communication (OCC) in two samples: undergraduate and graduate students. It was predicted that student-instructor tie strength (closeness) would lead to a greater number of modes used for OCC, and subsequently, the number of modes used for OCC would predict positive classroom outcomes, including communication satisfaction, cognitive and affective learning, and motivation. It was also predicted that the effect of closeness on the number of modes used for OCC would be moderated by student’s enjoyment of online communication, insofar as it would suppress the amount of modes used to communicate outside the classroom for those students who did not enjoy online communication, or amplify the effects for those students that did enjoy online communication. Results revealed that for undergraduate students, the number of media used to communicate with one’s instructor indirectly impacted their communication satisfaction, affective and cognitive learning, and motivation, through their feelings of the closeness with their instructor, contrary to the hypothesized model. This effect was strengthened for those students who had greater enjoyment of online communication. For graduate, the same pattern of indirect effects emerged, but enjoyment of online communication had no moderating effect in the graduate student sample. Implications for Media Multiplexity Theory (MMT) and viewing the student-instructor relationship as interpersonal are discussed. Because MMT was supported by the present studies, important conclusions on the nature of the student-instructor relationship, and the subsequent effects of their communication patterns are drawn

Setting the Mood: An Examination of the Roles of Romance-Related Mood, Situational Similarity, and Character Attribute Similarity in Selective Exposure to Romantic Comedies

Two studies were conducted in order to explore how romance-related mood, situational similarity, and character attribute similarity affect selective exposure to romantic comedies. Eight hypotheses were proposed based on traditional mood management theory (MMT). MMT predicts that people make media selection choices based on a desire to alter a negative mood state and achieve a positive mood state (Zillmann, 1988; Zillmann & Bryant, 1985). For this study in particular, MMT predicts that people in a negative romance-related mood would choose to avoid media content that reminds them of their negative romance-related mood. Content could remind participants of their negative romance-related mood through either situational similarity (Study 1) or character attribute similarity (Study 2). Situational similarity was operationalized through subgenre (female-led comedies vs. traditional romantic comedies), and character attribute similarity was operationalized through age. Experimental research was conducted with college-aged female participants in order to test the hypotheses. Results from a series of ANOVAs and hierarchical regressions revealed that, in general, the hypotheses proposed in this study were not supported. In fact, this study found results contrary to predictions made based on traditional MMT predicted outcomes. This suggests the need for future studies of MMT and its extensions, particularly in regard to motivations for counter-hedonic media selection choices

Facebook intensity, social network support, stability and satisfaction in long-distance and geographically-close romantic relationships:A test of a mediation model

The impetus for this study is the proposition that social network sites (SNSs), like Facebook, can be beneficial for romantic relationships via network support functions. This study investigated a model which proposes that the use of Facebook predicts relationship support from Facebook connections, and this, in turn, predicts relationship stability and satisfaction in romantic relationships. This mediation model was tested on data gathered via an online survey among individuals who use Facebook, who are in long-distance (LDRR, n = 142) and geographically-close romantic relationships (GCRR, n = 314). GCRR participants reported higher levels of Facebook intensity and relationship support, as well as perceived relationship stability and satisfaction than participants in LDRR. Moreover, the results indicated that Facebook intensity predicted higher access to Facebook relationship support in LDRR and GCRR which, in turn, predicted perceived relationship stability and satisfaction in LDRR; and only perceived relationship satisfaction in GCRR. However, Facebook intensity had direct negative impacts on relationship satisfaction in GCRR, and on perceived relationship stability in LDRR. Facebook intensity and Facebook relationship support were not associated with relationship stability in GCRR. This demonstrates the relative importance of SNSs, such as Facebook, in relationship stability for those in LDRR

Using social networks to understand and overcome implementation barriers in the global HIV response

Background: Despite the development of several efficacious HIV prevention and treatment methods in the past 2 decades, HIV continues to spread globally. Uptake of interventions is nonrandomly distributed across populations. Such inequality is socially patterned and reinforced by homophily arising from both social selection (becoming friends with similar people) and influence (becoming similar to friends). Methods: We conducted a narrative review to describe how social network analysis methods—including egocentric, sociocentric, and respondent-driven sampling designs—provide tools to measure key populations, to understand how epidemics spread, and to evaluate intervention take-up. Results: Social network analysis–informed designs can improve intervention effectiveness by reaching otherwise inaccessible populations. They can also improve intervention efficiency by maximizing spillovers, through social ties, to at-risk but susceptible individuals. Social network analysis–informed designs thus have the potential to be both more effective and less unequal in their effects, compared with social network analysis–naïve approaches. Although social network analysis-informed designs are often resource-intensive, we believe they provide unique insights that can help reach those most in need of HIV prevention and treatment interventions. Conclusion: Increased collection of social network data during both research and implementation work would provide important information to improve the roll-out of existing studies in the present and to inform the design of more data-efficient, social network analysis–informed interventions in the future. Doing so will improve the reach of interventions, especially to key populations, and to maximize intervention impact once delivered

Social Influence on the User in Social Network: Types of Communications in Assessment of the Behavioral Risks connected with the Socio-engineering Attacks

The purpose of this study is to study the impact of possible types of relationships between users, which are represented in the social network “VKontakte”, on the probability of the spread of a social engineering attack.Methods. To achieve this goal, a survey was developed and a web page was created, which is used to collect responses from respondents. After receiving the data, the obtained results were analyzed using the tools available in Microsoft Excel. In addition, for more in-depth analysis of the results, a C program was developed, which calculates the necessary characteristics and outputs the results to an Excel document.Results. In analyzing the results of the survey, the types of relationships between users were identified, in which they are more likely to respond to the request. It was also revealed that the answers are most often found in which several or even all categories in groups of relationship types between users were assigned the same assessments of the degree of readiness to respond to a request. In addition, it is worth noting that there are often answers in which respondents identified only one of the presented communication options.Conclusion. According to the study, it was hypothesized that the assessments of the degree of readiness to respond to a request to join the community for different groups of relationships are different, but the intragroup assessments differ little. The results obtained, demonstrating the lack of differentiation of values within groups of types of relationships, are significant, but at the same time, a deeper study of the orders that can be traced in the responses of a number of respondents is required