Omni-Opticon: a way of visualizing trend-proximities

George Shirk IV
David Dailey
Slippery Rock University

The Omni-Opticon is used to graph relationships between trendy topics in various topical sources (such as CNN and Twitter). It builds a dynamic relational network (graph) based on current topics that are trending at the moment. The topics are lexically analyzed in an attempt to recognize summarizing keywords. The diagram of relationships dynamically adjusts as topic change and show relations to other topics. Multiple ways are used to determine the inter-topic connectivity between other topics. One is to look at their .definitions. to see how closely related they are. Another is to look at words that are commonly co-occur in ordinary usage. The search engine BING is used to test for the proximity of topics through the numbers of matches to queries, using asynchronous calls to server-side queries of live web content. We believe that diagrams like these may provide interesting and informative views of the world.s rhythms as they unfold.

Omni-Opticon, the concept -- trends versus flukes

* How a phenomenon relates to the greater context of history determines, its longevity as a trend.
* Let's determine how phenomena interrelate.

Lexicography

Word relations 

Earlier work

words and their definitions moving about the screen  needs Internet Explorer (my fault)
A picture of the screen after the application has run for five minutes.

http://granite.sru.edu/~ddailey/wordtable.html
and
http://cs.sru.edu/~ddailey/svg/2011/wordtable2.htm


Bibliography

[REF1]  Dailey, David, An Analysis and Evaluation of the Internal Validity of the Remote Associations Test., , Educational and Psychological Measurement. 1978, 38:1031-1039.
[REF2] Dailey, David;  Gocal, Beverly, and Whitfield, Deborah. "Similarity Metric for Strings and Graphs". Proceedings of the 2010 Conference of the Pennsylvania Computer and Information Science Educators (PACISE), West Chester PA, 2010.
[REF3]  Dailey, David. The Extraction of a Minimum Set of Semantic Primitives from a Monolingual Dictionary is NP-Complete. Computational Linguistics, Volume 12, Number 4, 1986.