The tra­di­tional “broken win­dows theory” goes that acts of public dis­order in neighborhoods—such as graf­fiti, litter, and aban­doned homes—can encourage future crime there. But now research led by North­eastern Uni­ver­sity assis­tant pro­fessor Daniel T. O’Brien has lever­aged Big Data to shed new light on the fac­tors that pre­dict crime in urban neighborhoods.

The researchers found that, in fact, pri­vate con­flict may be a stronger pre­dictor of crime in a community.

Our research sug­gests that the ‘broken win­dows model’ doesn’t effec­tively cap­ture the ori­gins of crime in a neigh­bor­hood,” O’Brien said. “What’s hap­pening is that vio­lent crime is bub­bling out from the social dynamics of the com­mu­nity, out from these pri­vate con­flicts that already exist, and then is esca­lating and spilling into public spaces.”

O’Brien holds joint appoint­ments in the School of Public Policy and Urban Affairs and the School of Crim­i­nology and Crim­inal Jus­tice, and his research uses Big Data—most often in the form of large admin­is­tra­tive data sets gen­er­ated by city government—in con­junc­tion with tra­di­tional method­olo­gies to explore the behav­ioral and social dynamics of urban neigh­bor­hoods. This work is emblem­atic of his class­room teaching, as stu­dents in his Big Data for Cities course are immersed in the emerging field of “urban informatics.”

O’Brien is also the research director of the Boston Area Research Ini­tia­tive, which under­takes and sup­ports cutting-​​edge urban research at the inter­sec­tion of social sci­ence and public policy.

Assistant professor Dan O'Brien teaches in his Big Data for Cities course in December 2014. Photo by Brooks Canaday/Northeastern University

Assis­tant pro­fessor Dan O’Brien teaches in his Big Data for Cities course in December 2014. Photo by Brooks Canaday/​Northeastern University

The find­ings, O’Brien said, show how Big Data can be used to advance the study of neigh­bor­hood dynamics and to assess and mit­i­gate crime. His col­lab­o­ra­tors were Har­vard Uni­ver­sity pro­fes­sors Robert J. Sampson and Christo­pher Win­ship, who are director and co-​​director, respec­tively, of the Boston Area Research Initiative.

In a study with Sampson and Win­ship, O’Brien devel­oped an eco­metric method­ology that trans­lated more than 300,000 non-​​emergency calls to 311 in the city of Boston during 2011 and 2012 into mea­sures of phys­ical dis­order, such as graf­fiti and the accu­mu­la­tion of litter. The pur­pose of this method­ology, which was pub­lished this summer in the journal Soci­o­log­ical Method­ology, was to create a detailed set of met­rics for a city to use in assessing neigh­bor­hood dynamics sev­eral times a year.

Then, O’Brien and Sampson put the broken win­dows theory to the test by applying this method­ology to more than 1 mil­lion 311 and 911 calls in that same time period. The goal was to not only mea­sure social dis­order and crime, but to examine how it changed over time. The results, pub­lished this summer in the Journal of Research in Crime and Delin­quency, pointed to a “social esca­la­tion model” in which future dis­order and crime emerge not from public cues but from pri­vate dis­order within the community.

Using the 911 and 311 data the researchers devel­oped six measures—public social dis­order, public vio­lence not involving guns; domestic vio­lence and other pri­vate con­flicts; gun vio­lence, and pri­vate neglect in neigh­bor­hoods, and public den­i­gra­tion in neigh­bor­hoods. Upon exam­ining the con­nec­tions between these six fac­tors, here’s what they found:

•    Pri­vate con­flict was the strongest leading indi­cator of crime in the model, pre­dicting increases in social dis­order, public vio­lence, guns, and even phys­ical dis­order in pri­vately owned spaces.
•    Phys­ical and social forms of public dis­order were weakly pre­dic­tive of future vio­lence and dis­order, if at all; public den­i­gra­tion had no pre­dic­tive power, and the link from public social dis­order to later public vio­lence was half the mag­ni­tude of the reverse pathway from vio­lence to social disorder.

The researchers noted that the study did not demon­strate causality; in other words, why pri­vate con­flict was such a stronger indi­cator of crime than pri­vate neglect and public denigration.

O’Brien and his col­leagues the­o­rized that a stressful social ecology like that reflected in pri­vate con­flict among res­i­dents can drive behavior that leads to mul­tiple con­se­quences for a neigh­bor­hood as a whole. For example, friend­ship dis­putes or domestic vio­lence can spill out into the public space, and those inci­dents are likely to increase in severity over time—a pro­gres­sion that until now has been largely invis­ible to researchers because tra­di­tional forms of assess­ment such as neigh­bor­hood sur­veys or obser­va­tions only cap­ture what’s vis­ible in the public space and not what’s behind closed doors.

With these data sets, the method­ology becomes a tool for reli­ably and con­tin­u­ously tracking and ana­lyzing the con­di­tions of the city,” O’Brien said.

From the city to the class­room
O’Brien said the type of large admin­is­tra­tive data sets that proved to be cru­cial in these studies will be the focus of his Big Data for Cities course this fall. In this course, under­grad­uate and grad­uate stu­dents learn how to manage and ana­lyze large data sets—such as restau­rant inspec­tion vio­la­tion records and the tax assessor’s data­base for the city of Boston—by pur­suing group research projects focused on spe­cific city resources and services.

The course, which launched in fall 2014, dove­tails with the university’s new M.S. in Urban Infor­matics, which cou­ples com­pre­hen­sive data ana­lytics skills with an under­standing of the big ques­tions cities face in the 21st century.

What’s spe­cial about these Big Data is that we’re all still trying to figure out what to do with them, in terms of trans­lating them into soci­etal impact and improving munic­ipal ser­vices,” he said. “The stu­dents [last fall] were excited to take on this chal­lenge, and it’s been inspiring to see them draw out their ideas and conclusions.”