exploring enron – visualizing anlp results (an aanlp project)

exploring enron – visualizing anlp results (an aanlp project)Jeffrey Heer – jheer@cs.berkeley.edu

the problem ANLP technologies are highly valuable but

often less than usable and reliable… Can be hard to make sense of results… how

to go from reams of textual output to new knowledge and insight?

Completely automated processing can be dangerous! Can be wrong or obscure patterns, especially when trusted training data is not available.

one possible solution Turn ANLP technologies into tools usable

within exploratory data environments Enable users to directly visualize and analyze the

results of processing, always providing access to the underlying source data.

Users can then use these tools to further analysis, while simultaneously making their own decisions of the quality of processing results and possibly even correcting algorithms as they go.

visualize inferred social networkview message traffic and actual e-mail text

visualize clustering results – color coded to enron business e-mailspie charts indicate categorizations of e-mail traffic

zoom and pan to explore large networks

filter network for ‘hubs’ of higher connectivity

filter, zoom, details on demand! view all messages to or from a given person…

…or view all message traffic between two people.

networks form various communities … some obvious, some notcan we process the inferred network to automatically identify communties at various granularities?attempt social network analysis using a hierarchical agglomerative clustering approach, greedily combining groups into communities based on a criterion function that compares within-community edges against total connectivity.

show results of community analysis at various stages of progress… allowing interactive exploration of the agglomerative cluster tree

analysis scenario filtered graph to isolate “power players” looked for “california” color labels on edges found John Shelk reporting on congressional

meetings to Tim Belden – all one way e-mails looking at Time Belden revealed ALL one-

way e-mails sent to him, no responses, etc seemed a bit suspicious… where is that info

going?

Analysis scenario

All one way e-mails to Tim Belden about various legal issues…

guilty!

future work a plenty improved colors, filtering, and brushing

category filtering, brushing from e-mails to graph histogram visualization over sliders

visualize network of messages themselves? temporal dimension of data

time-selection range slider animate evolution of the network

search search search tie to additional analyses

automated clustering finer social network analysis duplicate identification, acronym resolution, etc…

please send me any ideas you have to improve this!!! jheer@cs.berkeley.edu

I’m Kenneth Lay. And I

approve this message.