Social Media Sensing (SMS 2017)
Motivation of the Track:
Billions of users daily interact with social media platforms like Facebook, Instagram, Pinterest, Twitter, Google+, etc. The checking of the preferred social media platform is becoming the first thing to do at wake up time, and the last thing to do before falling asleep. With no doubts, social media revolutionized the content ecosystem and the behavior of millions of people. Within social media, people communicate, collaborate and share information, and within Online Social Media Data (OSMD), it is possible to find contents and metadata about people, brands, products, services, personal preferences, issues, etc. Not surprisingly, OSMD are being used to understand people’s opinions and to measure citizens’ feelings. Indeed, this knowledge represents a critical factor in strategic decision processes, as it may be helpful in identifying problems and strengthening strategies. For instance, politicians may gauge the public mood to improve their political decisions, enterprise managers may increase customers engagement by tracking what people think about products and services, city administrators may analyze citizens’ opinions to enhance the life quality of the city, advertisers can improve the effectiveness of their messages by analyzing what people think of a brand. The use of OSMD to get insights about people and society is not trivial and covers many different disciplines, like computer science, social engineering, psychology, semiotics, and economics.
Topics of the Track:
This special section is seeking work in progress and position papers covering all aspects of Social Media Sensing. In particular, topics of interest include, but are not limited to:
- Accessibility and OSMD
- Advances in Social Media
- Big Data Analysis for OSMD
- Business Intelligence using OSMD
- Data Mining and Machine Learning for OSMD
- Decision-making models and OSMD
- Economics and Social effects
- Emotion Recognition
- Event forecasting based on OSMD data
- Fake news detection
- Games and Social Media
- Image Analysis
- Lexicon Design
- Prediction Analysis
- Privacy and Security in OSMD
- Recommendation systems for OSMD
- Reputation and Trust
- Sentiment Analysis
- Smart City
- Society Sensing
- Social Graph Analysis
- Social Media Trust
- Video Analysis
Organizers:
Marco Furini, Dipartimento di Comunicazione ed Economia, Università di Modena e Reggio Emilia, Italy
Silvia Mirri, Dipartimento di Informatica - Scienza e Ingegneria, Università degli Studi di Bologna, Italy
Technical Program Committee:
- Armir Bujari (University of Padua)
- Marco Furini (University of Modena and Reggio Emilia)
- Federica Mandreoli (University of Modena and Reggio Emilia)
- Riccardo Martoglia (University of Modena and Reggio Emilia)
- Silvia Mirri (University of Bologna)
- Betty J. Mohler (Max Planck Institute)
- Manuela Montangero (University of Modena and Reggio Emilia)
- Claudio Palazzi (University of Padua)
- Viviana Patti (University of Turin)
- Giovanni Pau (UPMC-LIP6, Paris)
- Marco Prandini (University of Bologna)
- Eva Oliveira (IPCA, Portugal)
- Francisco Rangel (University of Valencia)
- Marco Roccetti (University of Bologna)
- Paola Salomoni (University of Bologna)
- Maurizio Tesconi (CNR - Pisa)
- Mike Wald (University of Southampton)
- Gary Wills (University of Southampton)
