The research uses social media data from Twitter to develop a methodology for understanding the effects of events and conferences.

Key Findings

• Social media data offers a rich source of information to understand the effects of events on networking.
• Attending events is associated with a much higher rate of growth in Twitter connections among event participants than with people outside the event.
• Many of the connections formed at events are between people who already have a mutual connection on Twitter, indicating that they are more likely to have met in the longer-term.
• However, there are also connections between people that are further apart in the Twitter network before the event. This is particularly true for international connections.
• Within conferences one can see social networking behaviour consistent with commercial incentives e.g. consultants connecting with potential clients (but not with each other), or people connecting along language lines.

Historically, it has been difficult to obtain quantitative data on what happens at events. The widespread use of social media is however creating a rich source of data to understand them. It is also changing events allowing public conversations between participants and the wider world, and introducing a new medium for networking.

This research develops a methodology for using social media to understand events. The approach was developed using Twitter data from the LeWeb London tech festival. It can potentially used at any large conference/event where there is Twitter use (or other source of social network data). Its widespread adoption would allow a range of different measures of event effects to be obtained and benchmarked against each other.

The approach may be of interest to conference organisers wishing to understand their event (and the use of social media within it), for funders wishing to understand the impact of the conferences they support and to those deciding which event to go to (and how to network most effectively). Over time, it is hoped it will encourage a richer understanding of events, allowing them to be optimised to maximise innovation outcomes.

Authors

Hasan Bakhshi, John Davies, Juan Mateos-Garcia