Social collaboration via social tools – Social media to solve business problems

The following article will describe potential areas for research within the field of social networks and social collaboration in the enterprise scenario. The works from Smith, Hansen & Gleave (2009) in their paper “Analyzing Enterprise Social Media Networks” will be used as a research case that shows how social networks and Internet systems can be used as a strategic source for information in the company.

The phenomenon of social networking has moved into the workplace. According to a report from Next Vision IT Security is currently estimated that more than 300,000 companies worldwide use social networks for business purposes or as a tool for internal communication.  Enterprise social networks are poised to revolutionize how people interact in the workplace. Therefore, there is a pressing need to understand how people are using these social networks. (Jin, Hongyu & Friedman, 2013)

According to Smith, Hansen & Gleave (2009) “Social media tools provide a wealth of data that can be transformed into insights about the structure and dynamics of an enterprise or organization… Managers and analysts can use these metrics to better understand organizational dynamics, allowing them to better measure the effects of interventions and events.”

Smith, Hansen & Gleave (2009) supported the relevance of their research in that social network structures are created when people connect to one another through a range of ties. Therefore extracting, processing, and analyzing these networks can reveal important patterns in the structure and dynamics of the institutions.

In general terms, Smith, Hansen & Gleave (2009) approached their experiments by implementing various pieces of software known as social sensors, clickstream captures, feed subscription analysis and data mining. These computational mechanisms were able to collect, from the Internet, various aspects of people activities in the enterprise. Once the information was captured, a mathematical analysis was applied in the form of graph, behavior and content semantics. In their conclusion, the authors were able to determine the effect of social networking in the enterprise setting over revenues and project performance.

A similar study was performed by Ta-Shun, Hsin-Yu, Ling-Ching (2010). They observed a high-tech firm in Taiwan and demonstrated that the social network attributes of the firm itself can be examined to determine the relationships with the firm's profit and research and development capability.

In conclusion Smith, Hansen & Gleave (2009) built a formal model to relate the social interactions of the members of a company with the company’s metrics on performance. Regarding future challenges in the area, opportunities were found to develop the capacity of integrating teleconference (video and voice) and voice data into the network analysis. This area could provide an opportunity for the development of new algorithms for real time data extraction from streaming technologies. In addition, by Ta-Shun, Hsin-Yu, Ling-Ching (2010) recommendation, a future research agenda in the subject should include quantitative analysis of other high-tech industries.  Finally, as stated by Smith, Hansen & Gleave (2009), network visualization, especially visualizing it in large-scale and evolutionary manner, is also a challenge.

References

Jin, C., Hongyu, G., Li, L. E., & Friedman, B. (2013, 14-19 April 2013). Enterprise social network analysis and modeling: A tale of two graphs. Paper presented at the INFOCOM, 2013 Proceedings IEEE.

Next Vision IT Security (n.d). Use of Social Networks in the Enteprise Setting. Retrieved at http://www.nextvision.com/img/pdf/informe-redessociales.pdf

Smith, M., Hansen, D. L., & Gleave, E. (2009, 29-31 Aug. 2009). Analyzing Enterprise Social Media Networks. Paper presented at the Computational Science and Engineering, 2009. CSE '09. International Conference on.

Ta-Shun, C., Hsin-Yu, S., & Ling-Ching, Y. (2010, 18-22 July 2010). Social network analysis of directors and supervisors in Taiwan semiconductor industry. Paper presented at the Technology Management for Global Economic Growth (PICMET), 2010 Proceedings of PICMET '10:.