Location

RC 181

Start Date

1-8-2014 8:30 AM

End Date

1-8-2014 9:30 AM

Description

Today, there are masses of texts being generated and shared publicly such as microblogging Tweet streams and conversations; long-running blogs and wikis; open-ended text responses on large-scale surveys; digitally-released novels, and machine-generated texts (such as SciGen). In learning management systems, there are numerous threads of student-generated conversations. Text has long been plumbed for meaning—based on context and “close reading” by scholars. Of late, widely accessible computational tools have enabled text mining. AutoMap and ORA-NetScenes are tools created by CASOS (Center for Computational Analysis of Social and Organizational Systems) of Carnegie Mellon University that enable basic text mining and the visualization of networked text in 2D and 3D formats. AutoMap, a text-mining tool, offers some basic methods for sentiment analysis, the extraction of ngrams, the definition of network text relationships, and other revelatory insights.

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Aug 1st, 8:30 AM Aug 1st, 9:30 AM

Auto mapping texts for human-machine analysis and sense-making

RC 181

Today, there are masses of texts being generated and shared publicly such as microblogging Tweet streams and conversations; long-running blogs and wikis; open-ended text responses on large-scale surveys; digitally-released novels, and machine-generated texts (such as SciGen). In learning management systems, there are numerous threads of student-generated conversations. Text has long been plumbed for meaning—based on context and “close reading” by scholars. Of late, widely accessible computational tools have enabled text mining. AutoMap and ORA-NetScenes are tools created by CASOS (Center for Computational Analysis of Social and Organizational Systems) of Carnegie Mellon University that enable basic text mining and the visualization of networked text in 2D and 3D formats. AutoMap, a text-mining tool, offers some basic methods for sentiment analysis, the extraction of ngrams, the definition of network text relationships, and other revelatory insights.