Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:


What Online Social Networks May Know about Non-members

Heidelberg researchers study automatic generation of so-called shadow profiles

What can social networks on the internet know about persons who are friends of members, but have no user profile of their own? Researchers from the Interdisciplinary Center for Scientific Computing of Heidelberg University studied this question.

Any social network platform divides society into members and non-members. Relationships between non-members whose e-mail contact has been revealed by a member (red lines) can be accurately inferred based on relationships between members (black lines) and their connection patterns to non-members (green lines).
Picture: Ágnes Horvát

Their work shows that through network analytical and machine learning tools the relationships between members and the connection patterns to non-members can be evaluated with regards to non-member relationships. Using simple contact data, it is possible, under certain conditions, to correctly predict that two non-members know each other with approx. 40 percent probability.

For several years scientists have been investigating what conclusions can be drawn from a computational analysis of input data by applying adequate learning and prediction algorithms. In a social network, information not disclosed by a member, such as sexual orientation or political preferences, can be “calculated” with a very high degree of accuracy if enough of his or her friends did provide such information about themselves. “Once confirmed friendships are known, predicting certain unknown properties is no longer that much of a challenge for machine learning”, says Prof. Dr. Fred Hamprecht, co-founder of the Heidelberg Collaboratory for Image Processing (HCI).

Until now, studies of this type were restricted to users of social networks, i.e. persons with a posted user profile who agreed to the given privacy terms. “Non-members, however, have no such agreement. We therefore studied their vulnerability to the automatic generation of so-called shadow profiles”, explains Prof. Dr. Katharina Zweig, who until recently worked at the Interdisciplinary Center for Scientific Computing (IWR) of Heidelberg University.

In an online social network, it is possible to infer information about non-members, for instance by using so-called friend-finder applications. When new Facebook members register, they are asked to make available their full list of e-mail contacts, even of those people who are not Facebook members. “This very basic knowledge of who is acquainted with whom in the social network can be tied to information about who users know outside the network. In turn, this association can be used to deduce a substantial portion of relationships between non-members”, explains Ágnes Horvát, who conducts research at the IWR.

To make their calculations, the Heidelberg researchers used a standard procedure of machine learning based on network analytical structural properties. As the data needed for the study was not freely obtainable, the researchers worked with anonymised real-world Facebook friendship networks as a test set of basic data. The partitioning between members and non-members was simulated using a broad possible range of models. These partitions were used to validate the study results. Using standard computers the researchers were able to calculate in just a few days which non-members were most likely friends of each other.

The Heidelberg scientists were astonished that all the simulation methods produced the same qualitative result. “Based on realistic assumptions about the percentage of a population that are members of a social network and the probability with which they will upload their e-mail address books, the calculations enabled us to accurately predict 40 percent of the relationships between non-members.” According to Dr. Michael Hanselmann of the HCI, this represents a 20-fold improvement compared to simple guessing.

“Our investigation made clear the potential social networks have for inferring information about non-members. The results are also astonishing because they are based on mere contact data”, emphasises Prof. Hamprecht. Many social network platforms, however, have far more data about users, such as age, income, education, or where they live. Using this data, a corresponding technical infrastructure and other structural properties of network analysis, the researchers believe that the prediction accuracy could be significantly improved. “Overall our project illustrates that we as a society have to come to an understanding about the extent to which relational data about persons who did not provide their consent may be used”, says Prof. Zweig.

The results of the research were published in “PLoS ONE”.

Original publication:
Horvát E-Á, Hanselmann M, Hamprecht FA, Zweig KA (2012): One Plus One Makes Three (for Social Networks). PLoS ONE 7(4): e34740. doi:10.1371/journal.pone.0034740

Prof. Dr. Fred Hamprecht
Heidelberg University
Interdisciplinary Center for Scientific Computing
Phone: +49 6221 54-8800

Communications and Marketing
Press Office, phone: +49 6221 54-2311

Marietta Fuhrmann-Koch | idw
Further information:

More articles from Information Technology:

nachricht Next Generation Cryptography
20.03.2018 | Fraunhofer-Institut für Sichere Informationstechnologie SIT

nachricht TIB’s Visual Analytics Research Group to develop methods for person detection and visualisation
19.03.2018 | Technische Informationsbibliothek (TIB)

All articles from Information Technology >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: Space observation with radar to secure Germany's space infrastructure

Satellites in near-Earth orbit are at risk due to the steady increase in space debris. But their mission in the areas of telecommunications, navigation or weather forecasts is essential for society. Fraunhofer FHR therefore develops radar-based systems which allow the detection, tracking and cataloging of even the smallest particles of debris. Satellite operators who have access to our data are in a better position to plan evasive maneuvers and prevent destructive collisions. From April, 25-29 2018, Fraunhofer FHR and its partners will exhibit the complementary radar systems TIRA and GESTRA as well as the latest radar techniques for space observation across three stands at the ILA Berlin.

The "traffic situation" in space is very tense: the Earth is currently being orbited not only by countless satellites but also by a large volume of space...

Im Focus: Researchers Discover New Anti-Cancer Protein

An international team of researchers has discovered a new anti-cancer protein. The protein, called LHPP, prevents the uncontrolled proliferation of cancer cells in the liver. The researchers led by Prof. Michael N. Hall from the Biozentrum, University of Basel, report in “Nature” that LHPP can also serve as a biomarker for the diagnosis and prognosis of liver cancer.

The incidence of liver cancer, also known as hepatocellular carcinoma, is steadily increasing. In the last twenty years, the number of cases has almost doubled...

Im Focus: Researchers at Fraunhofer monitor re-entry of Chinese space station Tiangong-1

In just a few weeks from now, the Chinese space station Tiangong-1 will re-enter the Earth's atmosphere where it will to a large extent burn up. It is possible that some debris will reach the Earth's surface. Tiangong-1 is orbiting the Earth uncontrolled at a speed of approx. 29,000 km/h.Currently the prognosis relating to the time of impact currently lies within a window of several days. The scientists at Fraunhofer FHR have already been monitoring Tiangong-1 for a number of weeks with their TIRA system, one of the most powerful space observation radars in the world, with a view to supporting the German Space Situational Awareness Center and the ESA with their re-entry forecasts.

Following the loss of radio contact with Tiangong-1 in 2016 and due to the low orbital height, it is now inevitable that the Chinese space station will...

Im Focus: Alliance „OLED Licht Forum“ – Key partner for OLED lighting solutions

Fraunhofer Institute for Organic Electronics, Electron Beam and Plasma Technology FEP, provider of research and development services for OLED lighting solutions, announces the founding of the “OLED Licht Forum” and presents latest OLED design and lighting solutions during light+building, from March 18th – 23rd, 2018 in Frankfurt a.M./Germany, at booth no. F91 in Hall 4.0.

They are united in their passion for OLED (organic light emitting diodes) lighting with all of its unique facets and application possibilities. Thus experts in...

Im Focus: Mars' oceans formed early, possibly aided by massive volcanic eruptions

Oceans formed before Tharsis and evolved together, shaping climate history of Mars

A new scenario seeking to explain how Mars' putative oceans came and went over the last 4 billion years implies that the oceans formed several hundred million...

All Focus news of the innovation-report >>>



Industry & Economy
Event News

New solar solutions for sustainable buildings and cities

23.03.2018 | Event News

Virtual reality conference comes to Reutlingen

19.03.2018 | Event News

Ultrafast Wireless and Chip Design at the DATE Conference in Dresden

16.03.2018 | Event News

Latest News

For graphite pellets, just add elbow grease

23.03.2018 | Materials Sciences

Unique communication strategy discovered in stem cell pathway controlling plant growth

23.03.2018 | Agricultural and Forestry Science

Sharpening the X-ray view of the nanocosm

23.03.2018 | Physics and Astronomy

Science & Research
Overview of more VideoLinks >>>