The integration of several disciplines and their integration and deployment into the living environment are the ingredients for the design and development of future generation solutions. In this special issue, we intend to strengthen the link between the sentiment analysis field and the mental health research area. Within the Digital Health domain, several works demonstrated how the real-time monitoring of mood conditions led to an improvement of the overall patients and citizens quality of life. As an example, we want to mention the impact that emotion monitoring has on the improvement of daily healthy behavior (e.g. diet and physical activity) or how it works as a driver for reducing the exacerbation of undesired events for patients suffering from some chronic conditions.
One-on-one interviews have always constituted a common technique to derive meaningful insights to draw comprehensive analysis. This occurs in several domains. For example, in the business scenario, customer discovery is targeted by means of one-on-one interviews to obtain insights about product features, pricing and launching strategies. Also, within the health domain, clinical interview transcripts have been used to distinguish different patient behavior types and mental statuses in order to design effective interventions for many conditions and disorders. Or again, a client-centered counseling style for eliciting behavior change by helping clients to explore and resolve ambivalence. Therapists attempt to influence clients to consider making changes, rather than engaging in non-directive therapeutic exploration. Interviews help in providing qualitative analyses although they are subjective and are affected by the unconscious biases of the authors or the researchers. This may increase the burden of researchers especially when transcripts show a general trend derived from linear models. Approaches and techniques to identify the objectivity to the interpretation of personal interviews to derive significant insights are therefore needed. To note that an expanding collection of video clips have been released to aid in a deeper understanding of motivational interviewing, diversity and concepts of change. Starting from these, multi-modal future generation sentiment analysis systems should be devised to give the therapists all the possible information and emotional sphere of the patient and thus provide better counseling.
In this special issue we promote the submission of contributions integrating the sentiment analysis and mental health domains for empowering patients and domain experts in performing effective and efficient real-time monitoring of patients’ conditions. Finally, given the sensitivity of the data type treated within these systems, contributions on managing the privacy of emotional data are welcome.
The proposed special issue fosters interdisciplinary research for communities working on Artificial Intelligence, Semantic Web, Natural Language Processing, Image and Signal Processing, Big Data, Sensor Networks, Psychiatry and more joining their forces in order to develop Future Generation Sentiment Analysis Systems.
Last but not least, the special issue is sponsored by the PhilHumans and ValueCare projects. PhilHumans, https://www.philhumans.eu/, is a Marie Curie European Industrial Doctorate. Its aim is to train a next generation of young researchers in innovative Artificial Intelligence and establish users’ interaction with their personal health devices in an advanced and intuitive way by exploring cutting-edge research topics related to AI-supported human-machine interfaces for personal health services. While ValueCare, https://cordis.europa.eu/project/id/875215, aims to deliver efficient outcome-based integrated (health and social) care to older people facing cognitive impairment, frailty and multiple chronic health conditions in order to improve their quality of life (and of their families) as well as the sustainability of the health and social care systems in Europe.
Topics of Interest
Multi-modal Sentiment Analysis for motivational interviews
Natural Language Processing systems for interview transcripts
Image processing for clinical interviews
Video analysis for clinical interviews
Visualization or structural analysis of clinical interviews
Clustering algorithms for clinical interviews
Descriptive and linguistic analysis for clinical interviews
Opinion search for clinical interviews
Emotion detection and management
Emotional conversational agents
Multi-modal emotion detection
Sensor-based emotion detection
Knowledge-based emotion analysis
Authors are invited to submit original and unpublished papers. All submissions will be peer-reviewed and judged on accuracy, originality, significance, quality, and relevance to the special issue topics of interest. Submitted papers should not have appeared in or be under consideration for another journal. In case the work is based on a previous publication, only substantial extensions (at least 50%) will be considered acceptable for the Special Issue.
A mandatory cover letter has to be submitted together with the manuscript and it MUST contain a clear description of why the contribution is relevant for the Special Issue.
Furthermore, in case of an extension of a previous work, a detailed description of the differences and the new contributions in the new submission has to be included in the cover letter and also in the paper.
At the closing of the submission system, the Guest Editors will perform a pre-screening of all submissions to verify the requirements described above. Papers that will not meet such requirements, according to the Guest Editors discretion, will be rejected.
The pre-screening aims to admit no more than 20 papers to the first review round.
Paper submission due: December 1st, 2020, 23:59 Hawaii time
Desk reject notification by: December 15th 2020
First review round: January 31st, 2021
Revision due: March 19th, 2021
Final review decision: May 31st, 2021
Davide Buscaldi, University Sorbonne Paris Nord, France
Prof. Davide Buscaldi has been Associate Professor (Maître de conférences) at University Sorbonne Paris Nord (formerly Paris 13 University) since September 2012 and currently holds a part-time position as Assistant Professor at the Ecole Polytechnique, Computer Science Department (DIX). He is a member of the Knowledge Representation and Natural Language Processing group of the LIPN, the Computer Science Research laboratory of Sorbonne Paris Nord. He obtained his Ph.D. in Pattern Recognition and Artificial Intelligence from the Polytechnic University of Valencia, Spain, in 2010, ‘cum laude’ with a thesis on toponym disambiguation in Information Retrieval.
His main research interests cover the automatic or semi-automatic extraction and modelling of knowledge from texts, using supervised or unsupervised methods, semantic information retrieval, word sense disambiguation, geolocating information in text, and sentiment analysis, in particular regarding the detection of irony and humour in texts. He authored and co-authored more than 80 articles published in international peer-reviewed conferences and journals. In 2019 he received the best poster award at the 5th Franco-Polish forum for Innovation with a poster on Irony detection in Sentiment Analysis.
He is a member of the Human Language Technology group of the French Association for Artificial Intelligence, and has been an external reviewer for TU Dublin since January 2020. He is project coordinator for the Sorbonne Paris Nord University for the PhilHumans project. He has recently co-organized task 7 on Semantic Relation Extraction at SemEval 2018, he has co-chaired the challenges track at the European Semantic Web Conference (ESWC) 2018 and has been one of the co-organizers of the workshops on Deep Learning for Knowledge Graphs since ESWC 2019.
Mauro Dragoni, Fondazione Bruno Kessler, Trento, Italy
Dr. Mauro Dragoni (https://pdi.fbk.eu/people/profile/dragoni) is a research scientist at Fondazione Bruno Kessler within the Process and Data Intelligence research unit (PDI). His main research topics concern knowledge management, information retrieval, and machine learning by focusing on the development of real-world prototypes as the outcome of his research activities. Since 2015, he has been involved in activities dedicated to bring AI solutions within the Digital Health area and, in particular, by integrating sentiment analysis techniques into mental health monitoring systems. He has been involved in a number of international research projects, including Organic.Lingua (FP7), Medical CPS (EIT), PROMO (FESR), and Presto (FESR). He co-authored more than 120 scientific publications in international journals, conferences, and workshops. He organized several conferences, workshops, and special issues. He is co-organizer of the ACM SAC Track on Cognitive Computation in 2017 and 2018 and on Knowledge and Language Processing in 2019, 2020, and 2021. He co-organized the Challenge on Conceptual Sentiment Analysis co-located with ESWC 2015, 2016, and 2018; the Workshop on Emotion and Sentiment Analysis co-located with ESWC 2016, 2017, and 2018. He co-organized OWLED 2015 and he was the general chair of OWLED 2016. Then, he covered several organizational roles within the ESWC and ISWC conference series since 2014. He co-edited the Special Issue on “Applied cognitive computing: challenges, approaches, and real-world experiences” for the Progress in Artificial Intelligence journal and the Special Issue on “Knowledge and Language Processing” for the Information Processing and Management journal.
Flavius Frasincar, Erasmus University Rotterdam, the Netherlands
Dr. Flavius Frasincar is an assistant professor at Erasmus University Rotterdam, the Netherlands. He holds a PhD in Computer Science from Eindhoven University of Technology, the Netherlands. His research interests include Semantic Web, text/data mining, recommender systems, sentiment mining, and query optimization. He was involved in several EU and national projects among which TOWL, COMMIT, FERNAT, and SWEPS. Dr. Frasincar has multiple publications in the field of Web information systems, Semantic Web, natural language processing, and decision support systems. He also serves on the PC board of several Web, Semantic Web, databases, and natural language processing conferences as WWW, ICWE, EWSC, ISWC, NLDB, DEXA, and SAC. He is an editorial board member of DSS, IPM, IJWET, and CLINJ, and is co-editor-in-chief of JWE.
Dr. Flavius Frasincar organized several special issues for various journals among which DKE, IJWET, and JWE. He was the general chair of ICWE 2015, PC co-chair of NLDB 2017, and serves as vice-general chair for ICWE 2021. He organized two series of workshops WISM and IS-SWIS over many years. Five PhD students successfully defended their PhD thesis under his supervision. He has a Google h-index of 37 and more than 4500 citations in Google Scholar. He has published more than 50 journal papers and 150 conference/workshop papers in prestigious venues as TKDE, IEEE TCyb, CACM, JWS, DSS, IPM, and IS for journals, and WWW, WISE, ICWE, SAC, CIKM, ICDE, NLDB, and ESWC for conferences. Dr. Frasincar is a member of the Association for Computing Machinery.
Diego Reforgiato Recupero, University of Cagliari, Italy
Prof. Diego Reforgiato Recupero has been an Associate Professor at the Department of Mathematics and Computer Science of the University of Cagliari, Italy since December 2015, where he is director and creator of the Human-Robot-Interaction Laboratory (http://hri.unica.it), and co-director and creator of the Artificial Intelligence and Big Data Laboratory (http://aibd.unica.it), quality coordinator for the department and member of the Commission for start-up and spin-off of the University. He holds a double bachelor from the University of Catania in computer science and a doctoral degree from the Department of Computer Science of University of Naples Federico II. He got the National qualification for Computer Science Engineering and he is a Computer Science Engineer. In 2005 he was awarded a 3 year Post Doc fellowship with the University of Maryland where in 2006 he won the Computer World Horizon Award in the USA for the best research project on OASYS, an opinion analysis system that was commercialized by SentiMetrix (US company he co-founded). In 2008, he won a Marie Curie International Grant that allowed him to come back in Italy and was able to fund a 3 year Post Doc fellowship within the Department of Electrical, Electronic, and Computer Science Engineering (DIEEI) at the University of Catania where he won the “Best Researcher Award 2012” for a project about the development of a green router nearing commercialization. In the same year he got to the winning podium of the “Startup Weekend” event held in Catania with a project related to Opinion Analysis and was a winner of Telecom Italia Working Capital Award with a grant of 25k euros. In 2012 he co-founded the Italian company R2M Solution s.r.l. In 2013 he won a Post Doctoral Researcher position within the Semantic Technology Laboratory (STLAB) of the Institute of Cognitive Science and Technologies (ISTC) of the National Research Council (CNR) where he worked on Semantic Web and Linked Open Data; he is still an associated researcher at STLAB (ISTC-CNR), (http://stlab.istc.cnr.it/) where he collaborates within the Semantic Web and NLP domains. In 2013 he published a paper on Science related to the energy efficiency techniques in Internet. Besides SentiMetrix inc. (US company founded in 2007) and R2M Solution s.r.l. (Italian company founded in 2012), he co-founded R2M Solution ltd. (UK company founded in 2014), La Zenia s.r.l. (Italian company founded in 2014 for management of sports and recreational events), B-UP (Italian company founded in 2016 together with colleagues of CNR related to development of software within the Semantic Web domain) and VISIOSCIENTIAE (spin-off of the University of Cagliari founded in 2018 and related to the application of artificial intelligence to the financial domain). In 2018 together with Philips Research and other four European institutions he writes and wins PhilHumans, an European Industrial Doctorate Marie Curie whose goal is to train 8 international researchers in innovative Artificial Intelligence and establish user interaction with their personal health devices in an advanced and intuitive way. He is patent co-owner in the field of data mining and sentiment analysis (20100023311). He has industrial and consulting experiences in several national and international industries. He has research experience across a wide array of industrial, Italian, FP7 and H2020 research projects (with R2M about 30 funded FP7 and H2020 projects) most recently in the fields of ICT, Energy Saving in Telecommunication Networks and Smart Grids, Robotics and Semantic Web. He is author of more than 130 papers published within International Journals and Conference Proceedings. He has been involved in several workshops organizations (e.g. Workshop of Sentiment Analysis and Emotion detection within ESWC2014, ESWC2016, ESWC2017, ESWC2018, Workshop on Deep Learning and Knowledge Graphs within ESWC 2019, Workshop on Smart Personal Health Interfaces within ACM IUI 2020), Challenge organizations (e.g. Semantic Sentiment Analysis Challenge within ESWC2014, ESWC2015, ESWC2016, ESWC2017, ESWC2018), Special Issue Organizations (e.g. Special Issue “Semantic Web Technologies for Sentiment Analysis within Future Internet 2019, Special Issue on Machine Learning and Knowledge Graphs within FGCS 2020, Special Issue on Deep Learning and Knowledge Graphs within Semantic Web Journal 2020).