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Authors:Jayesh Prakash Gupta1;Hannu Kärkkäinen1;Karan Menon1;Jukka Huhtamäki1;Raghava Rao Mukkamala2;Abid Hussain3;Ravi Vatrapu4;Jari Jussila5;Henri Pirkkalainen1 andThomas Olsson6

Affiliations:1Unit of Information and Knowledge Management, Tampere University, Tampere and Finland;2Department of Digitalization, Copenhagen Business School, Copenhagen, Denmark, Department of Technology, Kristiania University College, Oslo and Norway;3Department of Digitalization, Copenhagen Business School, Copenhagen and Denmark;4Dept. of ITM, Ted Rogers School of Management, Ryerson University, Toronto, Canada, Department of Technology, Kristiania University College, Oslo and Norway;5HAMK Smart Research Unit, Häme University of Applied Sciences, Hämeenlinna and Finland;6Faculty of Information Technology and Communication, Tampere University, Tampere and Finland

Keyword(s):Tie Strength, Weak Ties, Social Media, Twitter, Facebook.

RelatedOntology Subjects/Areas/Topics:Artificial Intelligence ;Communication, Collaboration and Information Sharing ;Intelligent Information Systems ;Knowledge Management and Information Sharing ;Knowledge-Based Systems ;Social Networks and the Psychological Dimension ;Symbolic Systems ;Tools and Technology for Knowledge Management

Abstract:Tie strength is an essential concept in identifying different kind of social ties - strong ties and weak ties. Most present studies that evaluated tie strength from social media were carried out in a controlled environment and used private/closed social media data. Even though social media has become a very important way of networking in professional events, access to such private social media data in those events is almost impossible. There is very limited research on how to facilitate networking between event participants and especially on how to automate this networking aspect in events using social media. Tie strength evaluated using social media will be key in automating this process of networking. To create such tie strength based event participant recommendation systems and tools in the future, first, we need to understand how to evaluate tie strength using publicly available social media data. The purpose of this study is to evaluate tie strength from publicly available social media data in the context of a professional event. Our case study environment is community managers’ online discussions in social media (Twitter and Facebook) about the CMAD2016 event in Finland. In this work, we analyzed social media data from that event to evaluate tie strength and compared the social media analysis-based findings with the individuals’ perceptions of the actual tie strengths of the event participants using a questionnaire. We present our findings and conclude with directions for future work.(More)

Tie strength is an essential concept in identifying different kind of social ties - strong ties and weak ties. Most present studies that evaluated tie strength from social media were carried out in a controlled environment and used private/closed social media data. Even though social media has become a very important way of networking in professional events, access to such private social media data in those events is almost impossible. There is very limited research on how to facilitate networking between event participants and especially on how to automate this networking aspect in events using social media. Tie strength evaluated using social media will be key in automating this process of networking. To create such tie strength based event participant recommendation systems and tools in the future, first, we need to understand how to evaluate tie strength using publicly available social media data. The purpose of this study is to evaluate tie strength from publicly available social media data in the context of a professional event. Our case study environment is community managers’ online discussions in social media (Twitter and Facebook) about the CMAD2016 event in Finland. In this work, we analyzed social media data from that event to evaluate tie strength and compared the social media analysis-based findings with the individuals’ perceptions of the actual tie strengths of the event participants using a questionnaire. We present our findings and conclude with directions for future work.

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Paper citation in several formats:
Gupta, J. P., Kärkkäinen, H., Menon, K., Huhtamäki, J., Mukkamala, R. R., Hussain, A., Vatrapu, R., Jussila, J., Pirkkalainen, H. and Olsson, T. (2019).Identifying Different Types of Social Ties in Events from Publicly Available Social Media Data. InProceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - KMIS; ISBN 978-989-758-382-7; ISSN 2184-3228, SciTePress, pages 176-186. DOI: 10.5220/0008065501760186

@conference{kmis19,
author={Jayesh Prakash Gupta and Hannu Kärkkäinen and Karan Menon and Jukka Huhtamäki and Raghava Rao Mukkamala and Abid Hussain and Ravi Vatrapu and Jari Jussila and Henri Pirkkalainen and Thomas Olsson},
title={Identifying Different Types of Social Ties in Events from Publicly Available Social Media Data},
booktitle={Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - KMIS},
year={2019},
pages={176-186},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008065501760186},
isbn={978-989-758-382-7},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - KMIS
TI - Identifying Different Types of Social Ties in Events from Publicly Available Social Media Data
SN - 978-989-758-382-7
IS - 2184-3228
AU - Gupta, J.
AU - Kärkkäinen, H.
AU - Menon, K.
AU - Huhtamäki, J.
AU - Mukkamala, R.
AU - Hussain, A.
AU - Vatrapu, R.
AU - Jussila, J.
AU - Pirkkalainen, H.
AU - Olsson, T.
PY - 2019
SP - 176
EP - 186
DO - 10.5220/0008065501760186
PB - SciTePress

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