Friends - Face-to-Face vs. Social Media
“Study of Social Network ‘Check-Ins' Shows We Still Make Friends Face-To-Face”, Science Daily, 6 December 2012. The closer you live to another person, the more likely you are to be friends with them despite the growing use and impact of social media, according to a study that drew on data from the location-based social network provider Gowalla. The study, by researchers of the Social Cognitive Network Academic Research Center (SCNARC) at Rensselaer Polytechnic Institute [Troy, New York], also showed that people tend to move in groups of friends, and that two people chosen at random at a specific event (like a concert or at a particular store) are unlikely to be friends.
While the findings are seemingly common-sense, the study – and continued research on social networks – holds a powerful message for a broad range of applications that rely on accurate predictions of how people move, such as emergency planning, infrastructure development, communications networks, and disease control.
“The ramifications are extremely important because if we assume that people are moving randomly, we are wrong, and therefore we will not be prepared for what people actually do,” said Boleslaw Szymanski, director of SCNARC and the Claire and Roland Schmitt Distinguished Professor of Computer Science at Rensselaer. “Where you live really matters: Most of your friends are concentrated in the place where you live, and as the distance increases, this concentration rapidly drops.”
The findings also indicate that, even in the digital age, humans still form friendships based on personal interactions, said Tommy Nguyen, a Rensselaer graduate student and member of SCNARC.
“Even though, thanks to the Internet, you can be friends with anyone on the planet [who has access to the Internet], the likelihood that a person will be friends with someone in a distant location chosen at random is far lower than the likelihood that this person will be friends with someone who lives in close proximity,” said Nguyen. “Proximity creates a strong boundary for who will be your friends.”
The study, titled “Using Location-Based Social Networks to Validate Human Mobility and Relationships Models,” was awarded the best paper award at the Second Workshop on Social Network Analysis in Applications held earlier this year in Istanbul, Turkey, and has been published in the Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. The work is a continuation of the group's recent research concerning social networks. Last year, the group published an important paper showing that when just 10 percent of the population is committed to an opinion without comparable committed opposition, their opinion will quickly be adopted by the majority of the society.
Jennifer Platt, “Making Them Count: How Effective has Official Encouragement of Quantitative Methods been in British Sociology?”, Current Sociology, 2012, 60(5): 690-704. Britain’s Economic and Social Research Council (ESRC) has striven to increase the levels of quantitative work in British social science, but with little success shown in sociology journal articles. Why is this? A number of historical factors have contributed to this result: rapid recruitment in the 1960s of young faculty with little training, a tradition of doctorates without coursework, and the historical emergence of political and feminist critiques of quantification. It is evident that considerable persuasive and coercive resources were not sufficient to overcome intellectual resistance at the disciplinary and departmental level.
Christine Brickman Bhutta, “Not by the Book: Facebook as a Sampling Frame”, Sociological Methods & Research, 2012, 41(3): 57-88. Social networking sites and online questionnaires make it possible to do survey research faster, cheaper, and with less assistance than ever before. The methods are especially well-suited for snowball sampling of elusive sub-populations. This note describes the author's experience surveying thousands of Catholics via Facebook for less than a month, at little expense, and without hired help. Although the respondents were disproportionately female, young, educated, and religiously active, their responses preserved key correlations found in standard surveys conducted by Gallup and the GSS. The author relates her methods to existing Web-based methods and offers concrete suggestions for future work.
Johannes Illenberger and Gunnar Flötteröd, “Estimating Network Properties from Snowball Sampled Data”, Social Networks, 2012, 34(4): 701-711. This article addresses the estimation of topological network parameters from data obtained with a snowball sampling design. An approximate expression for the probability of a vertex to be included in the sample is derived. Based on this sampling distribution, estimators for the mean degree, the degree correlation, and the clustering coefficient are proposed. The performance of these estimators and their sensitivity with respect to the response rate are validated through Monte Carlo simulations on several test networks. Our approach has no complex computational requirements and is straightforward to apply to real-world survey data. In a snowball sample design, each respondent is typically enquired only once. Different from the widely used estimator for Respondent-Driven Sampling (RDS), which assumes sampling with replacement, the proposed approach relies on sampling without replacement and is thus also applicable for large sample fractions. From the simulation experiments, we conclude that the estimation quality decreases with increasing variance of the network degree distribution. Yet, if the degree distribution is not too broad, our approach results in good estimates for the mean degree and the clustering coefficient, which, moreover, are almost independent from the response rate. The estimates for the degree correlation are of moderated quality.
Paul DiMaggio and Filiz Garip, “Network Effects and Social Inequality”, Annual Review of Sociology, 2012, 38: 93–118. Students of social inequality have noted the presence of mechanisms militating toward cumulative advantage and increasing inequality. Social scientists have established that individuals' choices are influenced by those of their network peers in many social domains. We suggest that the ubiquity of network effects and tendencies toward cumulative advantage are related. Inequality is exacerbated when effects of individual differences are multiplied by social networks: when persons must decide whether to adopt beneficial practices; when network externalities, social learning, or normative pressures influence adoption decisions; and when networks are homophilous with respect to individual characteristics that predict such decisions. We review evidence from literatures on network effects on technology, labor markets, education, demography, and health; identify several mechanisms through which networks may generate higher levels of inequality than one would expect based on differences in initial endowments alone; consider cases in which network effects may ameliorate inequality; and describe research priorities.
Timo Lenzner, “Effects of Survey Question Comprehensibility on Response Quality”, Field Methods, 2012, 24(4): 409-428. Many studies have shown that vague or ambiguous questions are often interpreted idiosyncratically by respondents and thus can increase measurement error. This article provides some evidence that the cognitive effort required to comprehend survey questions affects data quality in a similar way. A Web survey experiment revealed that respondents receiving less comprehensible questions provided lower-quality responses (as indicated by break-off rates, number of non-substantive responses, number of neutral responses, and over-time consistency) than respondents receiving control questions that were easier to comprehend. Moreover, interaction effects of question comprehensibility with respondents’ verbal skills and their motivation to answer surveys were found. These findings indicate that survey designers should minimize the cognitive effort required to comprehend their questions and the article suggests specific ways how to do so.
Britta Busse and Marek Fuchs, “The Components of Landline Telephone Survey Coverage Bias. The Relative Importance of No-phone and Mobile-only Populations”, Quality and Quantity, 2012, 46(3): 1209-1225. The continuously growing mobile-only population raises concerns regarding the representativeness of traditional landline telephone surveys. At this time, the mobile-only population differs significantly from the general population, which leads to coverage bias when using fixed-line samples only for telephone surveys. However, in many European countries the mobile-only population is not the only source of coverage bias in telephone surveys. In addition, we have to consider coverage biases caused by considerable proportions of citizens without any telephone service. Since these two groups differ from the general population with respect to differential socio-demographic categories, in our view, the negative effects of mobile-only coverage error in traditional landline telephone surveys might in fact compensate – in part – for coverage bias caused by the no-phone population. To test this hypothesis of compensating coverage biases, we calculated relative coverage biases caused by the mobile-only population and relative coverage biases caused by the no-phone population in 30 European countries for two socio-demographic variables at two points in time. Results are presented for four groups of countries that differ with respect to no-phone and mobile-only rates. Results suggest that – in general – mobile-only biases and no-phone biases do not compensate to a great extent, and thus the alarming mobile-only biases cannot be neglected when using telephone surveys in the estimation of population parameters. Nevertheless, there are several countries where the bias caused by the mobile-only population is far bigger than the joint bias caused by the mobile-only population and the no-phone population. This finding suggests that biases caused by the recent mobile-only population would be even more severe if the no-phone population did not exist.
Casey A. Klofstad and Benjamin G. Bishin, “Exit and Entrance Polling: A Comparison of Election Survey Methods”, Field Methods, 2012, 24(4): 429-437. We report the results of an experiment in which voters participating in the 2008 presidential election were surveyed either as they exited their voting places (a traditional exit poll), or as they waited in line to vote (an “entrance poll”). To the best of our knowledge, the efficacy of entrance polling has not been studied previously. Our data show that the entrance poll, when compared to the exit poll, produced a significantly higher cooperation rate among voters and a significantly lower item nonresponse rate. In our discussion of these results, we examine the benefits and potential complications of entrance polling.
Denis Sassenroth, “The Impact of Personality Traits on the Willingness to Cooperate in Surveys - Evidence from the German General Social Survey in 2004, 2006, and 2008”, Methoden, Daten, Analysen - Zeitschrift für Empirische Sozialforschung, 2012, 6: 1 (Web-based only). According to the Social Isolation Hypothesis, socially isolated persons are less willing to participate in surveys. This paper argues that, in particular, subjectively experienced social isolation, as considered by the psychological concept of loneliness, affects the willingness to participate in surveys, and it further argues that loneliness depends upon personality traits. The hypothesis derived from this is that personality traits have an impact on cooperation willingness in surveys. This hypothesis is tested empirically by means of data from the German General Social Survey of the years 2004, 2006, and 2008. Negative effects of neuroticism and conscientiousness and positive effects of agreeableness and extraversion on cooperation willingness can be ascertained.
Jörg Blasius, “Comparing Ranking Techniques in Web Surveys”, Field Methods, 2012, 24(4): 382-398. In an experimental split ballot design, the author tests four different ranking techniques (drag and drop, numbering, arrows, and most-least) to explore potential effects on substantive answers, dropouts, and item nonresponse and response time between the groups. As an example, he uses six items from Inglehart’s materialism–postmaterialism index. Data come from 1,225 members of an access panel who entered the set of items to be rank ordered. With respect to sex, education, and age, there are no significant differences between the four experimental groups. However, the groups differ extensively in response time, item nonresponse, and estimation of the percentage of materialists and postmaterialists. Drag and drop is shown to be the best-suited method for collecting rank data in Web surveys.
Emanuela Sala, Jonathan Burton and Gundi Knies, “Correlates of Obtaining Informed Consent to Data Linkage: Respondent, Interview, and Interviewer Characteristics”, Sociological Methods & Research, 2012, 41(3): 414-439. In the United Kingdom, to link individual-level administrative records to survey responses, respondents need to give their consent. Using a unique set of respondent, interview, and interviewer characteristics derived from the British Household Panel Survey (BHPS) matched with an interviewer survey, this research investigates which characteristics influence consent to adding health and social security records to the survey responses. We find that consent is related to respondents’ attitudes to privacy, community mindedness and data linkage salience as well as to some interview features such as the “household contagion effect” and the survey “fidelity.” Interviewer characteristics, including their personality, attitudes to persuading respondents, and job experience, are not associated with consent. Interviewers’ survey experience in the current wave and their task-specific experience, however, do influence consent. Implications of the findings are discussed and areas for future research are identified.
Michel Rousseau, Marielle Simon, Richard Bertrand and Krystal Hachey, “Reporting Missing Data: A Study of Selected Articles Published from 2003–2007”, Quality and Quantity, 2012, 46(5): 1393-1406. Missing data (MD) is prevalent in empirical social science research. Furthermore, inconsistencies in the reporting and treatment of MD have been documented. The goal of the current project was to examine how MD was reported and treated in 68 studies issued from a refereed educational journal. It was observed that a fifth of the quantitative articles reviewed actually treated MD, using mainly deletion methods and only 10 percent of the explicit articles explained MD. Overall, MD reported or inferred averaged about 33 percent of cases and was commonly associated with missing subjects. Only three articles provided the actual percentages of MD. The results suggest that there may be a lack of consistency in how MD is reported and treated and that studies may remain deficient in how MD is addressed.
Clemens Kroneberg and Frank Kalter, “Rational Choice Theory and Empirical Research: Methodological and Theoretical Contributions in Europe”, Annual Review of Sociology, 2012, 38: 73–92. Rational choice theory (RCT) constitutes a major approach of sociological theorizing and research in Europe. We review key methodological and theoretical contributions that have arisen from the increasing empirical application of RCT and have the potential to stimulate the development of RCT and sociology more generally. Methodologically, discussions have evolved around how to test RCT empirically and how to realize its ambition to give theory-guidance to social research. These discussions have identified the strengths and shortcomings of direct and indirect test strategies using survey or experimental data. Meta-theoretically, different views have emerged about how to deal with counterevidence from applied fields of sociological research. Whereas some argue for a wide version of RCT that allows a broad set of auxiliary assumptions about preferences, expectations, and constraints, others advocate a major overhaul of RCT's core assumptions by incorporating additional concepts and mechanisms.
Robert M. Groves, Stanley Presser, Roger Tourangeau, Brady T. West, Mick P. Couper, Eleanor Singer and Christopher Toppe, “Support for the Survey Sponsor and Nonresponse Bias”, Public Opinion Quarterly, 2012, 76(3): 512-524. In an experiment designed to examine nonresponse bias, either the March of Dimes or the University of Michigan was identified as the sponsor of a survey mailed to individuals whose level of support for the March of Dimes was known. The response rate was higher to the university survey, but support for the March of Dimes increased survey participation to the same extent in both conditions. As a result of the overrepresentation of supporters of the organization, both surveys showed nonresponse bias for variables linked to support. The bias was greater, however, when the sponsor was identified as the March of Dimes. Thus, the university sponsor brought in not only more of the sample but also a more representative sample on variables related to support for the March of Dimes. Overall, the magnitude of the relationship between support for the organization and nonresponse was not a strong predictor of the magnitude of the nonresponse bias. The results demonstrate that the simple “common cause” model of nonresponse will not always apply, and that the model should be extended to incorporate multiple auxiliary variables.
Willem E. Saris, “Discussion Evaluation Procedures for Survey Questions”, Journal of Official Statistics, 2012, 28(4): 537–551. In this article, different criteria for the choice of an evaluation procedure for survey questions are discussed. Firstly, we mention a practical criterion: the amount of data collection the procedures require. Secondly, we suggest the distinction between personal judgments and model-based evaluations of questions. Thirdly, we suggest that it would be advantageous if the procedure could evaluate the following aspects of the questions: 1. The relationship between the concept to be measured and the question specified; 2. The effects of the form of the question on the quality of the question with respect to: a. the complexity of the formulation, b. the precision, c. possible method effects, d. many other characteristics; 3. The social desirability of some of the response categories. Besides that, it would be desirable if the procedure could indicate the effect of respondents’ lack of the knowledge about the topic on their answers. We compare 13 procedures for the evaluation of questions with respect to these criteria and will derive some conclusions from this overview.
Laurent Tambayong and Kathleen Carley, “Network Text Analysis in Computer-Intensive Rapid Ethnography Retrieval: An Example from Political Networks of Sudan”, Journal of Social Structure, 2012, 13, 2 (Web-based only). Advances in text analysis, particularly the ability to extract network based information from texts, is enabling researches to conduct detailed socio-cultural ethnographies rapidly by retrieving characteristic descriptions from texts and fusing the results from varied sources. We describe this process and illustrate it in the context of conflict in the Sudan. We show how network information can be extracted from vast quantities of unstructured texts-based information using computer-assisted processes. This is illustrated by an examination of changes in the political networks in Sudan as extracted from the Sudan Tribune. We find that this approach enables rapid high-level assessment of a socio-cultural environment, generates results that are viewed as accurate by subject matter experts, and match actual historical events. The relative value of this socio-cultural analysis approach is discussed.
Nigel G. Fielding, “Triangulation and Mixed Methods Designs: Data Integration with New Research Technologies”, Journal of Mixed Methods Research, 2012, 6, 2: 124-136. Data integration is a crucial element in mixed methods analysis and conceptualization. It has three principal purposes: illustration, convergent validation (triangulation), and the development of analytic density or “richness.” This article discusses such applications in relation to new technologies for social research, looking at three innovative forms of data integration that rely on computational support: (a) the integration of geo-referencing technologies with qualitative software, (b) the integration of multi-stream visual data in mixed methods research, and (c) the integration of data from qualitative and quantitative methods.
Oliver Lipps, “Using Information from Telephone Panel Surveys to Predict Reasons for Refusal”, Methoden, Daten, Analysen - Zeitschrift für Empirische Sozialforschung, 2012, 6, 1 (Web-based only). Refusing to complete a survey is the most important reason for nonresponse, both in cross-sectional and especially in panel surveys. To prevent (final) refusal, most surveys that use random samples implement some refusal conversion or refusal avoidance technique. Good experiences with the strategy of tailoring, such as adapting the treatment of sample members according to their characteristics, attitudes towards surveys, previous survey experiences and behavior, further motivates this.
