interactions and networks

For my data class,
essentially looking at different ways to visually show and describe data.

This is just a plot of people who visited a campus and what they spoke on, along with IDs uniquely referenced to each speaker.

This was actual live streamed Tw!tter information I imported

 I went further and essentially labelled these and used an algorithm (E!genvalues) to represent it better. I filtered my results based on keywords, and then clustered them on what the users that
were filtered through via the keyword had in common

 The commonalities of the clusters are shown here. For example, on the top left hand side,
notice that the three users have in common the one group based in France. The others
share LA and NY groups in common, with heavy clusters in one group or the other.

 Some of the raw data with visual mapping