A tweet. A product review on Amazon​.com. A Face­book pic­ture with a loca­tion stamp. All of these rep­re­sent dig­ital foot­prints left behind by online users, and col­lec­tively amount to large data sets—or so called “big data”—that researchers use to ana­lyze human behavior and social trends.

New assis­tant pro­fessor Christoph Riedl will take an inter­dis­ci­pli­nary approach to exam­ining these data to shed light on solu­tions to soci­etal chal­lenges in busi­ness and inno­va­tion. In par­tic­ular, he will apply his inter­ests in data sci­ence and com­pu­ta­tional social sci­ence to study sub­stan­tive research ques­tions in areas such as decision-​​making by indi­vid­uals and groups, online social net­works, and team­work and productivity.

I’m par­tic­u­larly drawn to how we can use modern com­mu­ni­ca­tion tools, through which large num­bers of people can work together, to solve existing prob­lems or tackle new prob­lems,” said Riedl, who joins the fac­ulty this fall with joint appoint­ments in the D’Amore-McKim School of Busi­ness and the Col­lege of Com­puter and Infor­ma­tion Sci­ence. Prior to North­eastern, he worked as a post-​​doctoral fellow at Har­vard Busi­ness School and Har­vard University’s Insti­tute for Quan­ti­ta­tive Social Science.

One of his ongoing projects is focused on word-​​of-​​mouth. While pos­i­tive online word of mouth is known to drive product sales, Riedl said less is known about what drives word-​​of-​​mouth itself. He exam­ined 280,000 online con­sumer reviews of more than 430 movies, focusing on the volume of and dis­agree­ment among pre­vi­ously posted film reviews. Fur­ther, he looked at how those fac­tors influ­ence whether someone new is likely to chime in and how pre­vious reviews may influ­ence the new reviewer’s take. He found that dis­agree­ment draws more people into the con­ver­sa­tion, but that people’s reviews are often influ­enced by what others have argued.

Iden­ti­fying such social influ­ence, he explained, can help researchers better under­stand the joint decision-​​making process in business.

In other research, Riedl is exploring whether social media activity can pro­vide the same rich, tan­gible social con­nec­tions formed in the real world. After sur­veying Twitter users and using data col­lected directly from Twitter to observe their online activity, Riedl and his col­leagues found that social aware­ness, social pres­ence, and usage fre­quency have a direct effect on social con­nect­ed­ness and do indeed help people build social capital.

Riedl will con­tinue to work on inno­v­a­tive projects like these as a member of the NULab for Texts, Maps and Net­works—the university’s research-​​based center for Dig­ital Human­i­ties and Com­pu­ta­tional Social Science.

To illus­trate the big-​​picture impli­ca­tions of big data, he noted that for example geo-​​location data from Twitter posts could help shed light on how indi­vid­uals and groups behave; how they migrate on a city level; and how their activity varies when they’re com­muting to work com­pared to when they’re relaxing on the weekend.

It’s a rich envi­ron­ment to study human behavior,” he said.