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#DISC2016 endorsed by INSNA: International Network for Social Network Analysis proudly announces its fourth annual conference to be hosted in Daegu, South Korea, on December 8-10th, 2016. DISC annual conference started in 2013, and attracted hundreds of scholars, industry leaders, and public sector experts from all around the globe. In 2016, #DISC2016 will have a special joint panel with the CeDEM ASIA 2016 on December 9, Friday. Government officials from Asian countries, leading scholars, and CEOs using open data are joining the special session.

 

Call for Papers

 

Submissions must include title, author information and contacts, abstract (300 word max.), and desired way of presentation (independent presentation or poster presentation).  Through a peer-review process, the papers presented or illustrated as a poster at #DISC2016 will be selected for internationally renowned journals (e.g., SSC and/or SCOPUS indexed journals).

 

Program Tracks
Submissions must include title, author information and contacts, abstract (300 word max.), and desired way of presentation (independent presentation or poster presentation), with a special focus on the following tracks:

 

Track 1. Network Science and Communication Research

Track Chair: Wayne Weiai Xu, University of Massachusetts Amherst (weiaixu@umass.edu)

 

The integration of Network Science and Communication research provides a unique way to understand social structures that shape human and organizational behaviors. Network insights reveal how individuals seek social capital and how embedded social reality shapes the perception of intimacy and trust. Network science is also a key to the track how information flows and innovation emerges through behavioral modeling and word-of-mouth. Beyond individual behaviors, organizations are also constrained and supported by a networked social reality. For example, organizations use social media networks for viral marketing.  As the development of computational technique allows us to extract increasingly large networks, it is critical to interpret meanings and messages behind various network shapes and outcomes. It is equally important to link prior findings and theories in communication research to new network analytics. We welcome creative and innovative high-quality submissions on (but are not restricted to) the following topics:

 

  • Theme 1: Combining Big Data and Small Data

This themes focus on bringing together quantitative and qualitative perspectives of communication research. Qualitative researchers can benefit from using computational skills to identify important small datasets, specific communities or demographics for in-depth analysis. Likewise, quantitative researchers can benefit from the richness of interpretative work to produce context-specific finding.

 

  • Theme 2: Network, Community and Integration

Our social network becomes fragmented, divided along ideological, religious and cultural lines. How do we bridge those divides? What network insights can we leverage to build a more integrated society. And against this backdrop, organizations and governments should strategically reach out to and understand different communities. This theme concerns the use of computational tools in data-driven public opinion and policy studies. In addition, concerns over privacy and security are of interest for this panel as well.

 

 

 

Track 2. New Knowledge Creation for Technology Change, Creativity and Organizational Innovation

Track Chair: Jae-Hwan Park, Middlesex University London (j.park@mdx.ac.uk)

 

In recent years, many studies have emphasized the knowledge creation and knowledge diffusion between university, firm and community leading to technological progress, economic development and social innovation during dynamic change and industry transition. The focal research point of knowledge creation and diffusion understands the specific process of how an individual, a group, an organization and a country create continuous knowledge creation and diffusion regimes along with establishing absorptive capacities. The understanding of such phenomena and hidden processes can be extended and investigated not only by the existing pervasive research approach, such as quantitative methodology based on patent and bibliography data, but also through qualitative research methodology, such as interviews and case studies. In particular, big data and its environment enable us to consider new approaches to understand innovation activities and new phenomena. We invite researchers from industrial and academic institutions to discuss new findings regarding knowledge creation and diffusion through various research approaches and in the wider contexts. We welcome creative and innovative high-quality submissions on (but are not restricted to) the following topics:

 

  • Big data and innovation as well as networks of innovators
  • New knowledge systems for economic and social change
  • Economic and technological catching up
  • University-Industry and Government-University-Industry relationship
  • Inter-firm collaboration and Innovation process of individual, firm and country
  • Innovation and knowledge diffusion
  • Innovation patterns and intellectual property rights
  • Innovation in industry transition, product, service industry, and service development 


 

Track 3. Trends in Data-Driven Marketing and Artificial Intelligence

Track Chair: Ke Jiang, University of California, Davis (kejiang@ucdavis.edu)

 

In recent years, big data has come to dominate the lexicon in marketing and the business landscape. It is the latest new industry being explored by entrepreneurs, which not only opens up new ways to mine the Web and social media for consumers and business but also creates challenges for industry to derive real business value from it. The job of the data-driven marketers is to extract out meaningful messages for the target audience, at the right time, and thus, stimulate desired consumer behavior. Artificial intelligence plays a significant role in efficiently and effectively exploring the richness of big data and increasing sales. We invite executives and data scientists from industry and research institutions to discuss trends in Data-Driven Marketing in the era of artificial intelligence, and also the impacts of advanced machining learning on the evolution of social science theory. We welcome creative and innovative high-quality submissions on (but are not restricted to) the following topics:

 

  • Applying machine learning to social science theories
  • Artificial Intelligence (AI) in shopping and customer service
  • Ethical issues in AI and Internet of things (IoT)
  • Breakthroughs in emotional understanding and digital marketing trends
  • Data analysis tools and marketing software as well as Data storage technology
  • Deep machine learning and user-friendly machine-learning
  • Management of metadata and master data (data about the data)
  • Smart business and mobile marketing
  • Technologies of converged platform and stream-analytics

 

 

Track 4. Entrepreneurial University Metrics

Track Chair: Pieter E. Stek, Delft Univ. of Technology, The Netherlands (pieter.stek@gmail.com)

 

Metrics and rankings are increasingly influencing decision-making in government, industry and academia. The combination of a competitive element and transparency has created a new and powerful social-communications paradigm, with rankings, reputation and reality all influencing each other to various degrees. Metrics and rankings have not just caught the imagination of policy makers, but also of professional bodies and the general public, to the extent that rankings releases have become media events. With the growth of open big data, the creation of indicators has been democratized. But this democratization also necessitates a discussion of the ethics, design principles and use of such indicators.

 

This session takes the concept of the Entrepreneurial University as its starting point, and aims to explore how metrics of science, entrepreneurship and social impact are informing the evolution of this concept, both in terms of its methodology and the discourse surrounding the Entrepreneurial University. Participants are invited to present original research about Entrepreneurial University and related metrics. Methodological, conceptual and critical contributions are warmly welcomed. We welcome creative and innovative high-quality submissions on (but are not restricted to) the following topics:

 

  • Triple Helix, innovation and entrepreneurship
  • Scientometrics/webometrics/infometrics/rankings
  • Academic and social impact
  • Open big data and its ethical uses

 

Important Dates/ Conference Venue 

Detailed information on the conference program and hotel/transportation will be provided soon.

 

  • Abstract submission deadline: July 1st, 2016
  • Notification of abstract acceptance: September 1st, 2016
  • Presentation file submission deadline: November 1st, 2016

 

 

Submissions and Awards
All abstracts should be submitted to the #DISC2016 submission page: https://easychair.org/conferences/?conf=disc2016

 

#DISC2016 encourages junior scholars and graduate students to apply for awards and travel grants. To be considered for the following awards and grants, send your full paper and biography no later than November 1st, 2016 to Co-Chair of #DISC2016, Kyujin Jung: kjung1@tnstate.edu 

 

  • Best Conference Paper, IMC Award I – $1,000 
  • Best Graduate Student Paper, IMC Award II – $500 
  • #DISC2016 Travel Grant and Scholarship Award – $500


Publications
There will be an independent folder “Special Issue: #DISC2016” in submission system of Selected Journals.

You are also welcome to submit your presentations to Journal of Contemporary Eastern Asia.

 

Other DISC (WATEF) related Special Issues:

 

 

Further Information and Contacts 

For any inquiry, please contact Co-Chair of #DISC2016, Kyujin Jung: kjung1@tnstate.edu