Conference PaperPDF Available

FeelCalc: a novel machine learning and data driven platform for the social web

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Abstract and Figures

Since 1990's the Internet has played the dominant role in the advancement of the modern world. With significant progress, also comes great responsibility for Artificial Intelligence (AI) and machine learning (ML) community. Moreover, human behavior on the Internet is often overlooked and is sometimes neglected by the corporate giants as they work in the best interest of their stockholders, not in the best interest of the ordinary people. As we are in an era of AI and ML we need to think carefully what type of platforms and system should we develop not for ourselves but the future generation? There is the enormous problem at stake academically: how can we optimize and strengthen the ML and data-driven platform for the social web that understands human emotions and feelings?
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T Furuta et al., J Pai n Relief 2016, 5:3(Suppl)
http://dx.doi.org/10.4172/2167-0846.C1.006
Internation al*Conferen ce*on*
Fibromyalgia and Chronic Pain (June 15-16, 2016 Philadelphia,
J Pain Relief
ISSN: 2167-0846 JPAR an open access journa
Fibromyalgia 2016
June 15-16, 2016
Volume 5, Issue 3(Suppl)
Page 40
FeelCalc: a novel machine learning and data driven
platform for the social web
Santosh Kalwar, Doctor of Science in Technology
Founder & CEO
Unelma Platforms, Espoo, Finland
Abstract (300 word limit)
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T Furuta et al., J Pai n Relief 2016, 5:3(Suppl)
http://dx.doi.org/10.4172/2167-0846.C1.006
Internation al*Conferen ce*on*
Fibromyalgia and Chronic Pain (June 15-16, 2016 Philadelphia,
J Pain Relief
ISSN: 2167-0846 JPAR an open access journa
Fibromyalgia 2016
June 15-16, 2016
Volume 5, Issue 3(Suppl)
Page 40
&
&
Biography (150 word limit)
Santosh Kalwar was born in Chitwan, Nepal, in 1982. He received the B.E. Degree in computer science and engineering from the Visvesvaraya Technological
University (VTU), Bangalore, India, in 2006, and MSc. (Tech), D.Sc. (Tech.) degrees in Human-Computer Interaction (HCI) from the Lappeenranta University of
Technology (LUT) Lappeenranta, Finland, in 2008 and 2014, respectively.
Dr. Kalwar currently works as a Founder & CEO of Unelma Platforms, which is an international software platform development company that aims to deliver
software to empower people. His current research interests include intelligent user interfaces, human-computer interaction, social computing, software
engineering, artificial intelligence, and big data. Dr. Kalwar is a Member of IEEE and ACM and serves as an external expert and reviewer for several top-tier
international journals, and conferences. He has received numerous grants, awards, and scholarships for his research. For more info about the author, please visit:
http://kalwar.com.np
Email: sk@unelma.ai
Contact number: +358440561437
Linked In linkedin.com/in/santoshkalwar
Twitter : @santoshkalwar
Notes/Comments:
We#are#glad#to#inform#you#that#your#abstract#entitled#"FeelCalc:#a#novel#machine#learning#and#data#driven#platform#for#the#social#web"#has#
been#approved#for#Oral#Presentation#at#our#conference#"6th#Global#Summit#on#Artificial#Intelligence#and#Neural#Networks"#scheduled#
on#October#15-16,#2018#in#Helsinki,#Finland.
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Thesis
Since the 1990’s, the Internet has played a central role in our daily lives. The Internet is an integral part of our personal, business, family, research, entertainment, academic and social life. However, there are social implications in using the Internet that are dependent on categories such as gender, age, ethnicity and cultural attributes. This social aspect can play a detrimental role in the expression of human anxiety on the Internet. An anxiety is a complex phenomenon that requires further elaboration. Thus, the aim of this thesis is to investigate human anxiety, or specifically, whether Internet anxiety can be conceptualized and measured. This thesis utilizes literature, qualitative and quantitative research methodologies, and a triangulation validation approach to conceptualize and measure the Internet anxiety phenomenon. In particular, the aim is to explore anxiety levels of Internet participants to develop and validate an Internet anxiety scale based on earlier research on Internet anxiety. The results of the dissertation present a two phase study. In Phase I, a smaller set of studies were conducted with a limited sample size. In Phase II, the research topic was investigated using 385 participants. Based on a number of studies or experiments, the state-of-the-art discovered in this thesis is creation, design, and validation of two scales, the Self-Assessment Scale (SAS) and a Modified Internet Anxiety Scale (MIAS) for measuring users’ anxieties on the Internet. The result of this dissertation is a conceptualization and measurement of various types of Internet anxiety and measurement of affective feelings of users on the Internet. As a proof-of-concept of measuring Internet anxiety, this thesis describes the author’s implementation of three sets of tools: MyAnxiety, introducing Internet anxieties types; Intelligentia, for collecting Internet anxieties types; and MyIAControl tool, implemented as a browser plug-in, for measuring affective feelings of users on the Internet. Conclusions drawn from the results show that these empirically validated scales and tools might be useful for researchers and practitioners in understanding and measuring the Internet anxiety phenomenon further.
Conference Paper
The Internet has recently emerged with new kind of services, applications and countless contents. User reaction plays essential role in interacting with the Internet. The theoretical concepts on feelings are extracted from psychology, phenomenology and computer science. It is understood that feelings are subjective experience of users aroused from different emotions. As feelings changes based on time, circumstance, people and environment, it is extremely difficult to assess feelings objectively. User's interaction on the Internet is based on contents (text, audio and video materials) and context (past experience, surroundings, circumstances, environment, background, or settings). Thus, the potential of understanding feelings and its measure is very important. In this paper, a systematic measure of feelcalc module is introduced to measure user's reaction in order to reduce human anxiety on the Internet.