SBP11 Day 2

I stayed in SBP11 for the whole day today, attending the keynote speaker sessions and all presentations. As it is a multi-disciplinary computer-modeling conference, I will not say I have interest in every topic presented. Here, I summarize my observation into four themes:


1. A few studies use social network analysis to identify the relationships among a group of people. Based on the frequency and pattern of communications and/or interactions, a social-network map can be drawn. This tactic could be used by federal agencies to identify the leaders of an organization (e.g. terrorist groups).

2. Some studies identify the frequently-used key words from a large data set (e.g. tweets) with data mining techniques, such as Latent Dirichlet Allocation (LDA). Social network analysis and LDA seems to be the “popular” methods.

3. There are more topics related to public health and medicare issues than I expected. Computer-modeling is a tool for data analysis. Where should these methods be used is researchers’ choice. Probably this is why this is multi-disciplinary conference.

4. In terms of planning a conference (event management), I feel the organizer put up a very good event. It is not a huge conference with thousands of attendees. The food was good. They are able to find a few sponsors to lower attendees’ costs --- registration fee is around $200 (I pay more than $600 for some other academic conferences); the conference was even able to provide some travel supports to students. I enjoyed the round table discussion session, where I could introduce myself to other experts and a few federal funding agencies. This conference informed me of several grant and collaboration opportunities.

Stay tuned for SBP11 Day 3. Dr. Bei Yu and I co-authored a paper entitled Toward Predicting Popularity of Social Marketing Messages in this conference, which will be presented in Day 3.

Relevant discussion: SBP11 Day 1

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