Objectives
In recent times, research activities in the areas of Opinion,
Sentiment, Emotion and/or Mood in natural language texts, speech, music
and other media have become the mainstream research under the umbrella
of subjectivity analysis and affective computing. These tasks are
considered vital since a decade from various academic and commercial
perspectives. The popularity of the Internet and the rapid expansion of
social media, a variety of user generated contents become available
online. However, the major challenges are how to process the user
generated contents such as texts, audio and images and how to organize
them in some meaningful ways.
The common interest areas where Artificial Intelligence (AI) meets
sentiment analysis can be viewed from four aspects of the problem and
the aspects can be grouped as Object identification, Feature
extraction, Orientation classification and Integration. The existing
reported solutions or available systems are still far from being
perfect or fail to meet the satisfaction level of the end users. The
main issue may be that there are many conceptual rules that govern
sentiment and there are even more clues (possibly unlimited) that can
convey these concepts from realization to verbalization of a human
being. Human psychology may provide the unrevealed clues and govern the
sentiment realization. The important issues that need attention include
how various psychological phenomena can be explained in computational terms and which AI concepts and computer methodologies will be proved
as the most useful ingredients from the psychologist's point of
view.
Sentiment analysis from natural language texts is a multifaceted and
multidisciplinary problem. Research efforts are being carried out for
identification of positive or negative polarity of the evaluative text
and also for the development of devices that recognize human affect,
display and model emotions from textual contents. Identifying strength
of sentiment in figurative texts or aspects and categories from the
reviews, detecting stance from the tweet data, identifying the
psychological condition of persons from chat even detecting sentiment
in clinical texts and the moods from music etc. are the recent trends
in the field of sentiment analysis.
Mood analysis from music is an emerging area in
Music Information Retrieval (MIR). The popularity of downloading and purchasing of music
from online music shops has been increased. Similarly, with rapid evolvement of technology,
music is just a few clicks away, on almost any personal gadget be it
computers, portable music players, or smart phones. This fact
underlines the importance of developing an automated process for its
organization, management, search as well as generation of playlists and
various other music related applications. Recently, MIR based on
emotions or moods has attracted the researchers from all over the world
because of its highly motivated implications in human computer
interactions.
In addition to Question Answering or Information Retrieval systems,
Topic-sentiment analysis is being applied as a new research method for
mass opinion estimation (e.g., reliability, validity, sample bias),
psychiatric treatment, corporate reputation measurement, political
orientation categorization, stock market prediction, customer
preference or public opinion study and so on. Techniques from
Artificial Intelligence play the important roles in these tasks.
In recent times, regular research papers continue to be published in
reputed conferences like , , , , , , and etc. The Sentiment Analysis
Symposiums are also drawing the attention of the research communities
from every nook of the world. There has been an increasing number of
efforts in shared tasks such as , , , , , , , , tracks since 2006, and
relevant NTCIR tracks since aimed to focus on different issues of
opinion and emotion analysis. Researches on Sentiment Analysis have
been performed in several languages other than English. The shared task
in 2015 has been organized to detect the sentiment from Bengali, Hindi
and Telugu tweets. The shared task in has also targeted sentiment
analysis in the languages like Arabic, Chinese, Dutch, French, Russian,
Spanish and Turkish including English. Some of the important names
e.g., and are the evaluation campaigns for the mood classification from
music using audio. The is one of the most reputed conferences in the
field of music and published many papers related to music mood.
Several communities from sentiment analysis have engaged themselves to
conduct relevant conferences, e.g., , in 2015, symposiums such as in
2015, and workshops such as , collocated with COLING-ACL 2006, in LREC
2008, , in CIKM 2009, in NAACL 2010, in EMNLP 2015, FLAIRS 2011 special
track on âAffect Computingâ�?, , in the satellite of LREC 2014, in
conjunction with KONVENS-2012 (PATHOS-2012), , , Workshop on , and a
bunch of special sessions like , , , in 2014 and so on.
Since our previous three workshops in conjunction with the
International Joint Conference on NLP (IJCNLP) in Chiang Mai, Thailand
during Nov. 7-13, 2011, International Conference on Computational
Linguistics (COLING) in Mumbai, India during Dec. 8-15, 2012, and with
the International Joint Conference on NLP (IJCNLP) in Nagoya, Japan
during the period October 14-18, 2013 were quite successful (with 20,
14, and 10 submissions and more than 30 participants from many
countries). Prof. Eduard Hovy and Prof. James Martin were the keynote
speakers for the first and second versions of this workshop
respectively. We are planning to conduct our next workshop in
conjunction with the International Joint Conference on Artificial
Intelligence (IJCAI) in New York, USA during July 9â15, 2023.
Inspired by the objectives we aimed at in the first three editions of
the workshop, the warm responses and feedbacks we received from the
participants and attendees and the final outcome, the purpose of the
proposed 4th edition of the Workshop on Sentiment Analysis where AI
meets Psychology (SAAIP 2023) is to create a framework for presenting
and discussing the challenges related to sentiment, opinion, emotion,
and mood analysis in the ground of NLP.
This workshop aims to bring together the researchers in multiple
disciplines such as computer science, psychology, cognitive science,
social science and many more who are interested in developing next
generation machines that can recognize and respond to the sentimental
states of the human users. The workshop will consist of a set of
invited talks and presentations of technical papers that will be
selected after peer review from the submissions received.
