Recent News & Events

Big Data in Industry: A New Way to Work

  • Event Date:
    Wednesday November 5th, 2014
  • Time:
    3:00pm
  • Location:
    Northeastern Visitors Center - West Village F, 1st Floor

Women who Inspire Speaker Series: Global Entreprenuers Driving Change

  • Event Date:
    Wednesday November 19th, 2014
  • Time:
    5:00pm
  • Location:
    Egan Research Center

Big Data, Innovative Research

In one sec­tion of Snell Library’s Dig­ital Media Com­mons on Monday after­noon, a large com­puter screen dis­played a daz­zling visu­al­iza­tion of a hypo­thet­ical out­break of a flu-​​like dis­ease orig­i­nating in Chicago. In another sec­tion of the room, vis­i­tors tested out an inter­ac­tive health coaching game designed to guide older adults through exer­cise rou­tines and pro­vide real-​​time feed­back. Else­where, dig­ital maps dis­played NASA satel­lite data used to detect trends in water avail­ability on a global scale.

These projects were among the many fea­tured at Northeastern’s sixth Pop Up Open Lab Expe­ri­ence and Recep­tion, where an inter­dis­ci­pli­nary group of fac­ulty and stu­dents pre­sented their inno­v­a­tive research that works with Big Data. The DMC served as a fit­ting host for the expo; located on Snell Library’s second floor, the cutting-​​edge work­space is a media lab and dig­ital cre­ativity center where stu­dents and fac­ulty can use a range of tech­nolo­gies such as new ani­ma­tion, audio and video editing, 3-​​D printing, and game-​​design software.

One area of the pop up lab fea­tured the work of net­work sci­en­tist Alessandro Vespig­nani, the Stern­berg Family Dis­tin­guished Pro­fessor of Physics, and his team at Northeastern’s MoBS Lab. They have devel­oped a com­pu­ta­tional model for visu­al­izing the spread of dis­ease by com­bining real-​​world pop­u­la­tion and human mobility data with elab­o­rate models on dis­ease trans­mis­sion. In par­tic­ular, Vespignani’s team is using this approach to track the Ebola out­break in West Africa and pre­dict its poten­tial spread globally.

Sev­eral other projects fea­tured are part of the NULab for Texts, Maps, and Net­works: the Viral Texts project, which seeks to dis­cover how par­tic­ular news sto­ries “went viral” in 19th-​​century news­pa­pers and mag­a­zines, the Early Caribbean Dig­ital Archive; and the Our Marathon: The Boston Bombing Dig­ital Archive project.

The event, titled “Aha! Making Sense from Big Data,” served as the latest install­ment of the Pop Up Open Lab series spon­sored by the Office of the Provost. Pre­vious events have fea­tured topics such as sus­tain­ability, the devel­op­ment of playable media, and per­sonal health tech­nolo­gies.

Other Big Data research fea­tured Monday at he event explores crit­ical urban infra­struc­ture sys­tems. Kris­tian Kloeckl, a new asso­ciate pro­fessor in the Depart­ment of Art + Design and the School of Archi­tec­ture, is inter­ested in designing inter­ac­tive visu­al­iza­tions that allow people to explore cities through the eyes of data. He pre­sented work he’s done in col­lab­o­ra­tion with col­leagues at MIT to create a data plat­form and visu­al­iza­tions com­bining real-​​time data from many of Singapore’s urban sys­tems operators—transit, telecom­mu­ni­ca­tions, taxis, to name a few.

He said this data could be used to iden­tify where to add more bus routes between bustling transit sta­tions or to help taxi com­pa­nies iden­tify loca­tions where more dri­vers are typ­i­cally needed during intense rain­storms, for example.

It’s all about bringing decision-​​making for the city more in sync with how the city actu­ally behaves,” he said.

Assistant professor Dietmar Offenhuber, right, talks with visitors about his research projects in which he's leveraged Big Data to examine and visualize waste management systems in the U.S. and abroad. Photo by Matthew Modoono.Dietmar Offen­huber, an assis­tant pro­fessor who holds joint appoint­ments in the Col­lege of Arts, Media and Design and the Col­lege of Social Sci­ences and Human­i­ties, show­cased two projects that involve using Big Data to visu­alize waste man­age­ment sys­tems in cities. In one project, he put GPS tracking devices on 3,000 pieces of trash from Seattle house­holds to map their move­ment over a two-​​month period. The other project took place in Brazil, where he used GPS data from trash col­lec­tors’ cell phones to map their col­lec­tion routes.

He said these projects help unveil the “invis­ible real­i­ties” of the urban land­scape and can help shed light on ways to make these sys­tems more effi­cient or orga­nized in entirely new ways that involve more stakeholders.

It’s about building bottom-​​up infor­ma­tion sys­tems for doc­u­menting waste man­age­ment,” Offen­huber said. “Glob­ally, one of the biggest prob­lems in waste man­age­ment is there’s hardly any data on it, and the same thing goes for other infra­struc­ture sys­tems as well.”

Study: Some Online Shoppers Pay More Than Others

Internet users reg­u­larly receive all kinds of per­son­al­ized con­tent, from Google search results to product rec­om­men­da­tions on Amazon. This is thanks to the com­plex algo­rithms that pro­duce results based on users’ pro­files and past activity. It’s Big Data at work, and it’s often advan­ta­geous for users. But such per­son­al­iza­tion can also be a dis­ad­van­tage to buyers, according to a team of North­eastern Uni­ver­sity researchers, when e-​​commerce web­sites manip­u­late search results or cus­tomize prices without the user’s knowledge—and which in some cases leads to some online shop­pers paying more than others for the same thing.

This trans­parency issue is at the core of a first-​​of-​​its-​​kind study co-​​authored by five North­eastern fac­ulty and stu­dents, including assis­tant pro­fes­sors Christo Wilson and Alan Mis­love of the Col­lege of Com­puter and Infor­ma­tion Sci­ence and pro­fessor David Lazer, who holds joint appoint­ments in CCIS and the Col­lege of Social Sci­ences and Human­i­ties.

In a new research paper, the team exam­ined 16 pop­ular e-​​commerce sites (10 gen­eral retailers and six hotel and car rental sites) to mea­sure two spe­cific forms of per­son­al­iza­tion: price dis­crim­i­na­tion, in which a product’s price is cus­tomized to the user; and price steering, in which the order of search results are cus­tomized to the user.

Overall, we find numerous instances of price steering and dis­crim­i­na­tion on a variety of top e-​​commerce sites,” the authors wrote.

Among their find­ings:
• The researchers found evi­dence of per­son­al­iza­tion on four gen­eral retailers and five travel sites, including cases where sites altered prices by hun­dreds of dol­lars. Overall, travel sites showed price incon­sis­ten­cies in a higher per­centage of cases, rel­a­tive to the con­trols.
• Cheaptickets and Orbitz imple­mented price dis­crim­i­na­tion by offering reduced prices on hotels to “mem­bers.”
• Expedia and Hotels​.com steered a subset of users toward more expen­sive hotels.
• Home Depot and Trav­e­locity per­son­al­ized search results for users on mobile devices.
• Price­line per­son­al­ized search results based on a user’s his­tory of clicks and pur­chases; users who clicked on or reserved low-​​price hotel rooms received slightly dif­ferent results in a dif­ferent order, com­pared to users who clicked on or reserved expen­sive hotel rooms or clicked on nothing. How­ever, because the dif­ferent orders did not cor­re­late to prices, this wasn’t con­sid­ered price steering.

Overall, most of the researchers’ exper­i­ments on the 16 e-​​commerce sites did not reveal evi­dence of price steering or price dis­crim­i­na­tion. But price dif­fer­ences were sig­nif­i­cant in some of the cases where they did find this evi­dence, and the researchers reported that they reached out to the six com­pa­nies iden­ti­fied in the study as imple­menting some form of personalization.

Their work—which will be pre­sented at the 2014 Internet Mea­sure­ment Con­fer­ence in Van­couver next month—represents the first com­pre­hen­sive study of e-​​commerce per­son­al­iza­tion that exam­ines price dis­crim­i­na­tion and price steering for hun­dreds of actual users as well as many more syn­thet­i­cally gen­er­ated fake accounts. The researchers selected what e-​​commerce sites to study based on informal rank­ings of the “top” sites. They noted that pop­ular sites such as Amazon and eBay were excluded because they func­tion as online mar­ket­places, while com­pa­nies like Apple were omitted from the study because they only sell their own products.

Wilson noted that he and his co-​​authors didn’t seek to judge whether these prac­tices are good or bad, stressing that price dis­crim­i­na­tion isn’t an inher­ently sin­ister ploy to take advan­tage of people. In fact, it hap­pens every day when someone gets a senior dis­count at the movies or a col­lege stu­dent gets a price break on books. Indeed, coupons are tech­ni­cally forms of price dis­crim­i­na­tion, he said. The key factor is whether these prac­tices are trans­parent. In most cases, dis­counts for select groups of people are clearly posted and widely under­stood, but the North­eastern researchers said such behavior is much harder to detect on e-​​commerce sites.

This unknown served as the pri­mary inspi­ra­tion for the team’s study, which was con­ducted in April and May. The team exam­ined each site’s activity for typ­i­cally over a two– to three-​​week period. The researchers devel­oped a sophis­ti­cated method­ology that set a range of con­trols to ensure that they could accu­rately iden­tify evi­dence of price dis­crim­i­na­tion and price steering.

Here’s how it worked: Let’s say you want to buy a hammer through Sears’ online site. Not only would you search for it using your per­sonal laptop or smart­phone, but you would also fire off iden­tical queries at the exact same time from clean accounts devoid of cookies and search and pur­chase his­tory. In theory, the results should be iden­tical. There might be what is referred to as “noise”—inconsistencies that aren’t due to per­son­al­iza­tion but rather other fac­tors such as changes in inven­tory or the geo­graphic diver­sity of the dat­a­cen­ters housing these e-​​commerce sites. But if the “noise” in your laptop search is greater than the “noise” in the syn­thetic accounts, then you’ve got price dis­crim­i­na­tion or steering.

The higher-​​level goal of the group’s research, Wilson said, is to study the effect of per­son­al­iza­tion algo­rithms on the Web, which goes hand-​​in-​​hand with the pro­lif­er­a­tion of Big Data.

I get this ques­tion from people all the time: ‘How do I get the best price?’ The truth is I don’t have a good answer,” Wilson said. “It changes depending on the site, and the algo­rithms they use change reg­u­larly. Good advice today might not be good advice tomorrow. The point is that as a con­sumer, you’re at a dis­ad­van­tage unless it’s transparent.”