Social media play a central role in many people’s lives, and they also have a profound impact on businesses and society. Users post vast amounts of content (text, photos, audio, video) every minute. This user generated content (UGC) has become increasingly multimedia in nature. It documents users’ lives, revealing in real time their interests and concerns and activities in society. The analysis of UGC can offer insights to individual and societal concerns and could be beneficial to a wide range of applications, for example, tracking mobility in cities, identifying citizen’s issues, opinion mining, and much more.

In contrast to classical media, social media thrive by allowing anyone to publish content with few constraints and no oversight. Social media posts thus show great variation in length, content, quality, language, speech and other aspects. This heterogeneity poses new challenges for standard content access and analysis methods. On the other hand, UGC is often related to other public information (e.g. product reviews or discussion of news articles), and there often is rich contextual information linking, which allows for new types of analyses.

In this seminar, we aim at discussing the specific properties of UGC, the general research tasks currently operating on this type of content, identifying their limitations and lacunae, and imagining new types of applications made possible by the availability of vast amounts of UGC.

We will identify specific properties of UGC such as presentation quality and style, bias and subjectivity of content, credibility of sources, contradictory statements, and heterogeneity of language and media.

We will discuss current applications exploiting UGC, like e. g. sentiment analysis, noise removal, indexing and retrieving UGC, recommendation and selection methods, summarization methods, credibility and reliability estimation, topic detection and tracking, topic development analysis and prediction, community detection, modeling of content and user interest trends, collaborative content creation, cross media and cross lingual analysis, multi-source and multi-task analysis, social media sites. Live and real-time analysis of streaming data, and machine learning for big data analytics of UGC. These applications and methods involve contributions from several data analysis and machine learning research directions.

We will imagine new applications exploiting UGC in areas such as e.g. marketing, political campaigns, crisis management, eHealth, customer reviews for shopping, socio-political analyses, smart city, user mobility analysis, and user profiling.

The general goal of this seminar is to collect, discuss and understand the state-of-the-art in research on UGC, to identify unresolved problems and to define a research agenda for further work in this area. We are especially interested in properties, tasks, and applications that span multiple content types or different social media systems.

About three months before the seminar, we will ask invited participants to fill out an online questionnaire, describing their specific interest in the topic, naming crucial and urgent research issues, stating their willingness to give a survey talk or give a more specific presentation, as well as proposing working group topics. Based on this input, we will schedule about 4-5 longer survey talks, each followed by a few short, specialized presentations from the respective areas. In addition, we will reserve at least two half days for working group sessions on topics chosen by the participants.

Creative Commons BY 3.0 DE

Tat-Seng Chua, Norbert Fuhr, Gregory Grefenstette, Kalervo Järvelin, and Jaakko Peltonen

• Tat-Seng Chua (National University of Singapore, SG) [dblp]
• Nicolas Diaz-Ferreyra (Universität Duisburg-Essen, DE) [dblp]
• Gerald Friedland (University of California - Berkeley, US) [dblp]
• Norbert Fuhr (Universität Duisburg-Essen, DE) [dblp]
• Anastasia Giachanou (University of Lugano, CH) [dblp]
• Tatjana Gornostaja (tilde - Riga, LV) [dblp]
• Gregory Grefenstette (IHMC - Paris, FR) [dblp]
• Iryna Gurevych (TU Darmstadt, DE) [dblp]
• Andreas Hanselowski (TU Darmstadt, DE) [dblp]
• Xiangnan He (National University of Singapore, SG) [dblp]
• Benoit Huet (EURECOM - Sophia Antipolis, FR) [dblp]
• Kalervo Järvelin (University of Tampere, FI) [dblp]
• Rosie Jones (Microsoft New England R&D Center - Cambridge, US) [dblp]
• Rianne Kaptein (Crunchr - Amsterdam, NL) [dblp]
• Krister Lindén (University of Helsinki, FI) [dblp]
• Yiqun Liu (Tsinghua University - Beijing, CN) [dblp]
• Marie-Francine Moens (KU Leuven, BE) [dblp]
• Josiane Mothe (University of Toulouse, FR) [dblp]
• Wolfgang Nejdl (Leibniz Universität Hannover, DE) [dblp]
• Jaakko Peltonen (Aalto University, FI) [dblp]
• Isabella Peters (ZBW – Dt. Zentralbib. Wirtschaftswissenschaften, DE) [dblp]
• Miriam Redi (NOKIA Bell Labs - Cambridge, GB) [dblp]
• Stevan Rudinac (University of Amsterdam, NL) [dblp]
• Markus Schedl (Universität Linz, AT) [dblp]
• David Ayman Shamma (CWI - Amsterdam, NL) [dblp]
• Alan Smeaton (Dublin City University, IE) [dblp]
• Benno Stein (Bauhaus-Universität Weimar, DE) [dblp]
• Lexing Xie (Australian National University - Canberra, AU) [dblp]