The 5th IEEE International
Conference on Data Science
and Advanced Analytics

1–4 October 2018
Turin — Italy

SeCredISData – Sentiment, Emotion, and Credibility of Information in Social Data


10:30 - 16:00, room “Piemonte”
  • 10:30Introduction to the Special Session (Organizers)
  • 10:45Keynote presentation: “Stance and Misogyny: Analysing Cases of Hate Speech”
    Paolo Rosso, Universitat Politècnica de València, Spain
  • 11:30“Willingness to Share Emotion Information on Social Media: Influence of Personality and Social Context”
    Damien Dupre, Nicole Andelic, Gawain Morrison and Gary Mckeown
  • 12:00“'Behind the words': psychological paths underlying the un/supportive stance toward immigrants in social media environments
    Francesca D'Errico, Paciello Marinella and Matteo Amadei
  • 12:30Conference lunch
  • 14:00“A Methodological Template to Construct Ground Truth of Authentic and Fake Online Reviews”
    Snehasish Banerjee
  • 14:30“An Empirical Analysis of the Role of Amplifiers, Downtoners, and Negations in Emotion Classification in Microblogs”
    Roman Klinger and Florian Strohm
  • 15:00“Utilizing Information from Tweets for Detection of Sentiment-based Interaction Communities on Twitter”
    Alron Jan Lam and Charibeth Cheng
  • 15:30“Portability of Aspect Based Sentiment Analysis: Thirty Minutes for a Proof of Concept”
    Luca Dini, Paolo Curtoni and Elena Melnikova

Keynote Speaker

Paolo Rosso
Universitat Politècnica de València,

“Stance and Misogyny: Analysing Cases of Hate Speech”

Once upon a time we believed in the wisdom of crowds and that we could learn from what others discussed in social media. Nowadays, we are not so sure about it. Comments in social media often lack of aurgumentation and users do not try to persuade others to agree with their claim by presenting evidence. Communication is mostly with users belonging to the same community with the risk of an intellectual isolation (filter bubble), where beliefs may be reinforced by a repeated message inside the closed community (echo chamber). When users communicate with someone who disagrees with their viewpoints, they often do it spewing hateful comments behind a veil of anonymity. This may only increase political and social polarization and extremism. In this keynote, we will show some cases of hate speech in Twitter we came across in the datasets of two shared tasks we organized at IberEval on stance detection and misogyny identification. We will also comment how some participants detect them.

Aims and Scope

The Social Web represents nowadays the principal means to support and foster social interactions among people through Web 2.0 technologies. Individuals interact in virtual communities to pursue mutual interests or goals, by exchanging multiple kinds of contents (i.e., textual, acoustic, visual), the so-called User-Generated Content (UGC). In this context, the SeCredISData Special Session is especially devoted to discussing the implications that Data Analysis has in tackling open issues related to society, and in developing applications able to tackle these issues.

On the one hand, the focus of the Special Session will be given to the study and the application of affective computing and sentiment analysis to social data, which can impact on monitoring, analyzing and counteracting discrimination and hate speech, which are increasingly spreading phenomena in our countries also in combination with the pervasiveness of social media. Furthermore, also the applications of sentiment analysis and emotion detection in social media for the development of education, entertainment, health, e-government, and games will be considered as interesting object of investigation.

On the other hand, by considering the process of “disintermediation” that affects social media, the Special Session will also investigate the problem of assessing the credibility of information spreading among and across virtual communities. The diffusion of fake news, hoaxes, rumors, fake reviews, inaccurate health information, can have a negative impact on society with respect to different aspects, from influencing political elections, producing harmful effects if connected to the health of patients, to generating hate and discrimination phenomena. For all these reasons, the study and the development of approaches that can help people in automatically assess the level of credibility of information is a fundamental research issue in the last years.

The aim of this Special Session is therefore to cover different aspects related to Data Analysis applied to social data, by addressing to a heterogeneous community of researchers who has data science as a common denominator.

Topics of Interest

Areas of interest to DSSA 2018 include, but are not limited to:

  • Subjectivity, sentiment, and emotion detection in social media and big data
  • Sentiment-based indexing, search, and retrieval in social media
  • Sentiment topic detection & trend discovery
  • Multimodal emotion and sentiment detection in social media
  • Big data for multimodal affective interaction (e.g., chatbots)
  • Time evolving opinion & sentiment analysis
  • Emotions, sentiment, geographic locations and places
  • Using sentiment and affect for social media predictive analysis (including genre identification, political preference, etc.)
  • Irony and sarcasm detection
  • Emotion models and ontologies of emotions
  • Affect in natural language
  • Hate speech detection
  • Information fusion for affective computing
  • Summarization and visualization of emotions, sentiment and affective data
  • Applications of sentiment analysis and emotion detection in social media to education, entertainment, health, e-government, games
  • Ethical issues in affect and opinion detection in user-generated contents
  • Opinion spam, group spam, fake news detection
  • Credibility/reliability of health-related information
  • Fact-checking
  • Multimedia content credibility
  • Information/misinformation diffusion
  • Trust and reputation in virtual communities
  • Retrieval of credible information
  • Gold standard datasets generation with respect to the credibility of information
  • Crowdsourcing credibility


Farah Benamara
Toulouse University,

Cristina Bosco
University of Turin,

Elisabetta Fersini
University of Milano-Bicocca,

Gabriella Pasi
University of Milano-Bicocca,

Viviana Patti
University of Turin,

Marco Viviani
University of Milano-Bicocca,

Contact Persons

Farah Benamara –
Cristina Bosco –
Elisabetta Fersini –
Gabriella Pasi –
Viviana Patti –
Marco Viviani –

This site uses third parties' cookies.
If you want to know more or deny your consent to all or some of the cookies click here.
If you access any element below this banner you consent to the use of cookies.