About

Scott Feld is a Professor of Sociology at Purdue University, with a Ph.D. from Johns Hopkins University obtained in 1976. His specialization includes social networks, individual and collective decision-making, and evaluation research. Dr. Feld has served as Assistant to Full Professor of Sociology at the State University of New York at Stony Brook from 1975 to 1991, and as Professor of Sociology at Louisiana State University from 1991 until 2004 before joining Purdue University in 2004. He has published over sixty articles, including twelve in the most prestigious journals in Sociology and Political Science. His ongoing research interests involve the causes and consequences of patterns in social networks, processes of individual and collective decision-making, and applications of sociology, most recently including innovations in marriage and divorce laws such as covenant marriage. He regularly teaches undergraduate and graduate courses on social networks, research methods, and statistics.

Research topics

• Sociology
• Computer Science
• Psychology
• Political Science
• Social psychology
• Public relations
• Computer network
• Ecology
• World Wide Web
• Medicine
• Epistemology
• Biology
• Engineering
• Cognitive science
• Data science

Selected publications

• On the friendship paradox and inversity: A network property with applications to privacy-sensitive network interventions

  Proceedings of the National Academy of Sciences · 2024-07-19 · 4 citations

  articleOpen accessSenior author

  We provide the mathematical and empirical foundations of the friendship paradox in networks, often stated as "Your friends have more friends than you." We prove a set of network properties on friends of friends and characterize the concepts of ego-based and alter-based means. We propose a network property called inversity that quantifies the imbalance in degrees across edges and prove that the sign of inversity determines the ordering between ego-based or alter-based means for any network, with implications for interventions. Network intervention problems like immunization benefit from using highly connected nodes. We characterize two intervention strategies based on the friendship paradox to obtain such nodes, with the alter-based and ego-based strategy. Both strategies provide provably guaranteed improvements for any network structure with variation in node degrees. We demonstrate that the proposed strategies obtain several-fold improvement (100-fold in some networks) in node degree relative to a random benchmark, for both generated and real networks. We evaluate how inversity informs which strategy works better based on network topology and show how network aggregation can alter inversity. We illustrate how the strategies can be used to control contagion of an epidemic spreading across a set of village networks, finding that these strategies require far fewer nodes to be immunized (less than 50%, relative to random). The interventions do not require knowledge of network structure, are privacy-sensitive, are flexible for time-sensitive action, and only require selected nodes to nominate network neighbors.

  PublisherOA PDFDOI

• You are only as safe as your riskiest contact: Effective COVID-19 vaccine distribution using local network information

  Preventive Medicine Reports · 2022-04-05 · 1 citations

  articleOpen accessCorresponding

  When vaccines are limited, prior research has suggested it is most protective to distribute vaccines to the most central individuals - those who are most likely to spread the disease. But surveying the population's social network is a costly and time-consuming endeavour, often not completed before vaccination must begin. This paper validates a local targeting method for distributing vaccines. That is, ask randomly chosen individuals to nominate for vaccination the person they are in contact with who has the most disease-spreading contacts. Even better, ask that person to nominate the next person for vaccination, and so on. To validate this approach, we simulate the spread of COVID-19 along empirical contact networks collected in two high schools, in the United States and France, pre-COVID. These weighted networks are built by recording whenever students are in close spatial proximity and facing one another. We show here that nomination of most popular contacts performs significantly better than random vaccination, and on par with strategies which assume a full survey of the population. These results are robust over a range of realistic disease-spread parameters, as well as a larger synthetic contact network of 3000 individuals.

  PublisherDOI

• Human social sensing is an untapped resource for computational social science

  Nature · 2021 · 98 citations

  • Computer Science
  • Sociology
  • Data science
  PublisherOA PDFDOI

• Interventions with Inversity in Unknown Networks Can Help Regulate Contagion

  arXiv (Cornell University) · 2021 · 1 citations

  Senior authorCorresponding
  • Computer Science
  • Computer Science
  • Computer network

  Network intervention problems often benefit from selecting a highly-connected node to perform interventions using these nodes, e.g. immunization. However, in many network contexts, the structure of network connections is unknown, leading to a challenge. We develop and examine the mathematical properties of two distinct informationally light strategies, a novel global strategy and local strategy, that yield higher degree nodes in virtually any network structure. We further identify a novel network property called Inversity, whose sign determines which of the two strategies, local or global, will be most effective for a network. We demonstrate that local and global strategies obtain a several-fold improvement in node degree relative to a random selection benchmark for generated and real networks (including contact, affiliation and online networks). In some networks, they achieve a 100-fold improvement. We show how these new strategies can be used to control contagion of an epidemic spreading across a set of village networks, finding that the strategies developed here require far fewer ($<50\%$) nodes to be immunized, relative to the random strategy baseline. Prior research has typically used the complete network structure to choose nodes for optimal seeding. The relevant network is often costly to collect, and is privacy-invasive, requiring knowing each person's network neighbors, and might not be possible to obtain for time-sensitive interventions. Our interventions are less invasive of individual privacy, since each selected node only needs to nominate some network neighbors for intervention, while mathematically guaranteed to provide better connected nodes.

  PublisherOA PDFDOI

• Reflections on “The Focused Organization of Social Ties” and its Implications for Bonding and Bridging

  Cambridge University Press eBooks · 2021 · 4 citations

  1st authorCorresponding
  • Sociology
  • Political Science
  • Sociology

  We appreciate this opportunity to reiterate and more fully explicate the "focus theory" as first presented in "The Focused Organization of Social Ties" (Feld 1981) and extended in "Social Structural Determinants of Similarities among Associates" (Feld 1982) and in "The Structured Use of Personal Associates" (Feld 1984). We have been gratified to see that so many social network analysts have used the focus theory in their own work. Nevertheless, we believe that we can now better elucidate some of the fundamental assumptions, processes, and implications in a way that we hope will make the theory more useful to more researchers in more different modes going forward.

  PublisherDOI

• Egonets as systematically biased windows on society

  Network Science · 2020 · 12 citations

  1st authorCorresponding
  • Sociology
  • Social psychology
  • Psychology

  Abstract A person’s egonet, the set of others with whom that person is connected, is a personal sample of society which especially influences that person’s experience and perceptions of society. We show that egonets systematically misrepresent the general population because each person is included in as many egonets as that person has “friends.” Previous research has recognized that this unequal weighting in egonets leads many people to find that their friends have more friends than they themselves have. This paper builds upon that research to show that people’s egonets provide them with systematically biased samples of the population more generally. We discuss how this ubiquitous egonet bias may have far reaching implications for people’s experiences and perceptions of frequencies of other people’s ties and traits in ways that may influence their own feelings and behaviors. In particular, these egonet biases may help explain people’s tendencies to disproportionately experience and overestimate the prevalence of certain types of deviance and other social behaviors and consequently be influenced toward them. We illustrate egonet bias with analyses of all friends among 63,731 Facebook users. We call for further empirical investigation of egonet biases and their consequences for individuals and society.

  PublisherDOI

• Chapter 14 Social Networks Structural Focus Theory

  Stanford University Press eBooks · 2020-12-31

  book-chapter1st authorCorresponding
  PublisherDOI

• Evidence Required to Know Whether Marriage Promotion Increases Other Social Benefits

  Journal of Family Theory & Review · 2018-08-22 · 4 citations

  article1st authorCorresponding

  Abstract For marriage promotion interventions to be effective, social policy for increasing other social benefits (e.g., child welfare, family financial self‐sufficiency), they must increase numbers and/or quality of marriages in such a way to produce those other social benefits. Evidence should show that particular interventions (a) produce increases in numbers and/or quality of marriages, (b) produce increases in other benefits, and (c) produce increases in other benefits through the changes in marriages described in (a). There is some evidence that marriage promotion interventions have produced small increases in numbers and quality of marriages, but there is little evidence regarding the extent to which these interventions have produced other intended social benefits. We describe the nature of additional data and analyses that would enable us to determine the extent to which marriage promotion interventions are effective ways to increase other social benefits.

  PublisherDOI

• Separate, Unequal, and Uncorrelated: Why We Need to Consider Race-specific Homicide Rates in US Metropolitan Areas

  Socius Sociological Research for a Dynamic World · 2018-01-01 · 4 citations

  articleOpen access1st authorCorresponding

  Sociologists recognize that American metropolitan areas continue to be highly segregated by race and that blacks continue to experience much higher homicide rates than whites across metropolitan areas. We show that the racial divide goes beyond separate and unequal to the point of being uncorrelated. Based on data from the Centers for Disease Control Underlying Cause of Death files 2008–2010 and the American Community Survey, this paper reports that homicide rates for whites and blacks are uncorrelated across US metropolitan areas. We show that under these conditions, the practice of analyzing overall homicide rates can substantially misrepresent both subgroups and that the correlations of other variables with overall homicide rates systematically exaggerate the average of the correlations with the two separate homicide rates. We therefore suggest that it is crucial to analyze rates of black and white homicide separately to accurately describe and understand causes and consequences of urban homicide.

  PublisherOA PDFDOI

• Escalation and Desistance from Wife Assault in Marriage

  2017-09-04 · 15 citations

  book-chapter1st authorCorresponding

  Over half of American couples experience one or more incidents of assault between the partners during the course of a marriage. The rates of desistance and escalation among these couples can be compared with the rates among couples without intervention. The findings confirmed the hypothesis, which specified a high rate of desistance, even for husbands who had frequently used severe violence. Intervention might involve reduction of stress, provision of social and material support, and efforts to increase equality between spouses and change values that tolerate minor violence. The link between "minor" violence and "severe" violence is a controversial aspect of research on family violence. It would be useful to specifically know whether reducing minor assaults could reduce the likelihood of major violence. Experiments could be done involving intervention with couples reporting minor violence. Divorce and separation are important causes of sample attrition, and divorce and separation are known to be associated with marital violence.

  PublisherDOI

Frequent coauthors

• Bernard Grofman

  University of California, Irvine

  82 shared

• Nicholas R. Miller

  12 shared

• Guillermo Owen

  9 shared

• Guillermo Owen

  State University of New York

  9 shared

• Joel I. Grossman

  8 shared

• Natalie Masuoka

  6 shared

• Thomas L. Brunell

  4 shared

• William Koetzle

  3 shared

Education

• PhD, Sociology

  Johns Hopkins University

  1976

• BS, Mathematics

  Stony Brook University

  1970