SOCIAL COMPUTING – WHEN KNOWLEDGE BECOMES SOCIAL
mail Elisabeth Lex Research Area Manager
mail Matthias Traub Business Area Manager
Social networks and media, such as Facebook and Twitter & Co., shape our communications and knowledge sharing more than ever. In the "Social Computing" Area we investigate the benefits and added value that they can offer companies and institutions. Area Social Computing addresses issues associated with knowledge extraction and construction and utilization of social network data with the objective to deliver the relevant information to businesses and the users.Our goal is to utilize the resources of the digital age for human benefit
For the Graz-based Agency Blanc Noir, we are developing a recommendation system and novel algorithms that analyze big data to provide the user with targeted and tailored products or advertising – and, considering his/her social interactions, only the kind that the user may be interested in. “This way we can simultaneously address customers of online shops or internet platforms in order to provide them with personalized information and thereby raise the Internet shopping experience to a new level,” says Stefan Kahr, Managing Director of Blanc Noir.
For the Styrian company Exthex, we are developing innovative social media marketing methods to increase customer loyalty to its products. In this context, we not only create marketing strategies based on social network analysis, but also novel recommender mechanisms and algorithms in this domain.
Within the project Organic Lingua, knowledge construction and structuring is enhanced by enriching resources with metadata to facilitate the exchange and delivery of information in organic agriculture. In this context, we are developing new services, such as knowledge construction based on Natural Language Processing (NLP) techniques and collaborative filtering methods.
With Know-Center as the scientific coordinator, within the project Web Information Quality Evaluation Initiative (WiQ-Ei) an international consortium is developing algorithms and methods to assess the quality of social media and web content based on various criteria, such as factual density, sentiment, objectivity and trust. This way, we help individuals and businesses to assess the reliability and relevance of the social media and web content.
As a member of the Network of Excellence STELLAR, Know-Center particularly contributes to analyzing interaction networks within the scientific community. Via these networks, areas of interest can be determined and experts in each area can be recommended. We use our expertise in Science 2.0, social network analysis and machine learning to assist the scientific community in the best possible way.