Special Issue: Deep Intelligence for Social Media Analytics

Theme and Scope

Social Media has become a unique source of information for various activities such as finding solutions for queries, exploring the opportunities for socio-economic information sharing and thus being a critical part of the information environment providing an extraordinary outreach to all kind of the public users. It is projected that social media will continue to enable new fascinating applications and revolutionize many existing ones, provided with the continuing interest and meta-information which is ever growing, generated through it.

Recent advancements in Deep Intelligence enabled the Social Media Analytics to perform the sampling of data from multimodal spatial environment to provide the good characterization of big data. This need for social media analytics emerged due to the defining characteristics of Web 2.0 which provides content generation and information dissemination in the social media in huge volumes due to the technological platforms of Internet and Mobile Technologies. From the application point of view, significant research interests have been evolved on social media due to its challenges and opportunities in the past few years and thus it has become a multidisciplinary in nature. Hence the focus of this social media research turned up towards social media analytics and intelligence.

The development and evaluation of informatics tools and frameworks to collect, observe, analyze, review, and visualize social media data, generated from a target application is the major focus of social media analytics. The objective of social media analytics study is to: promoting conversations and interaction amongst online communities and extracting meaningful patterns and intelligence to assist entities in the live conversation. The goal of social media intelligence is to extract actionable data from social media with developing decision-making frameworks and providing design and solution architectural frameworks for emerging applications in the web. Despite growing interest from corporations and other communities, research towards social media intelligence found to be in early stage only. In the research perspective, collaborative discussions were carried out on the various dimensions in the concepts of social media intelligence, its major technical challenges and the implementation tools, still there is lack of research in systematic way and proven results.

Since much of social media intelligence research is undertaken in application contexts with the goal of supporting decisions, it necessitates well-articulated and well defined performance parameters. However, quantifying these indicators in a wide range of situations where social media intelligence could be useful is difficult. Hence there is a rich demand of research interests in addressing dynamic decision making, solving uncertainty problems and optimized modelling. Also, the researchers likely need to put their efforts to develop novel computational frameworks and implementation strategies, extracting relevant data streams with ranking and scores based on user input and conversations thus enhancing the quality measures.

The aim of this special issue is to model the state of the art in social media intelligence with analytical research that directly encompasses the Artificial Intelligence methodologies to extract user dialogues and analyse with concrete decision making strategies. Original research and review articles in this area are encouraged in the following topic areas including, but are not limited to:

  • Semantic Social Media Analytics -  Stream based view
  • Human centred computing for social interactions among users
  • Social media intelligence – Key issues and challenges in data driven approaches
  • Technical and Social challenges and opportunities in Social media Intelligence – Application Perspective
  • Deriving actionable information from social media – Tools and Frameworks
  • Quantifying performance measures in Social media Intelligence
  • Future event Prediction by social media analytics
  • Human behaviour prediction in social networks – Deep Learning approaches
  • Social Network Analysis – Survey on methodologies
  • Pattern extraction from user conversation – Deep Learning Applications
  • Frameworks for dynamic decision making in social media intelligence
  • Modeling frameworks in social media – Latent feature learning

Instructions for Manuscripts

Each paper, written in English, the maximum words number in each paper should be below 8,000 words, including references and illustrations. More information can be found at https://jit.ndhu.edu.tw/. Before submission authors should carefully read over the journal’s Author Guidelines, which are located at https://jit.ndhu.edu.tw/about/submissions#authorGuidelines.

Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at https://mc04.manuscriptcentral.com/internet-tech.  When submitting papers, authors should specify that the manuscript is for Special Issue on “Deep Intelligence for Social Media Analytics”. The manuscript template can be found at https://jit.ndhu.edu.tw/about/submissions#authorGuideline.

Important Dates

Paper Submission Deadline: 

14 February 2022  April 20, 2022

Author Notification: 25 April 2022

Revised Papers Submission: 30 June 2022

Final Acceptance: 04 September 2022

Tentative Publication: The 1st quarter of 2023

Guest Editors

Dr. Muhammad Attique Khan [Leading Guest Editor]

Computer Science Department, HITEC University, Pakistan

Email: attique.khan@hitecuni.edu.pk, attique.khan@ieee.org


Dr. Seifedine Kadry 

Department of Applied Data Science, Noroff University College, Norway

Email: seifedine.kadry@noroff.no


Dr. Gaurav Dhiman 

Department of Computer Science, Government Bikram College of Commerce, India

Email: gaurav.dhiman@thapar.edu


Dr. Imran Razzak 

School of Info Technology, Deakin University, Australia

Email: imran.razzak@deakin.edu.au