abstract: Internet and social media devices created a new public space for debate on political
and social topics (Papacharissi 2002; Himelboim 2010). Hotly debated issues
span all spheres of human activity; from liberal vs. conservative politics, to radical
vs. counter-radical religious debate, to climate change debate in scientific community,
to globalization debate in economics, and to nuclear disarmament debate in
security. Many prominent ’camps’ have emerged within Internet debate rhetoric and
practice (Dahlberg, n.d.).
In this research I utilized feature extraction and model fitting techniques to process
the rhetoric found in the web sites of 23 Indonesian Islamic religious organizations,
later with 26 similar organizations from the United Kingdom to profile their
ideology and activity patterns along a hypothesized radical/counter-radical scale, and
presented an end-to-end system that is able to help researchers to visualize the data
in an interactive fashion on a time line. The subject data of this study is the articles
downloaded from the web sites of these organizations dating from 2001 to 2011,
and in 2013. I developed algorithms to rank these organizations by assigning them
to probable positions on the scale. I showed that the developed Rasch model fits
the data using Andersen’s LR-test (likelihood ratio). I created a gold standard of
the ranking of these organizations through an expertise elicitation tool. Then using
my system I computed expert-to-expert agreements, and then presented experimental
results comparing the performance of three baseline methods to show that the
Rasch model not only outperforms the baseline methods, but it was also the only
system that performs at expert-level accuracy.
I developed an end-to-end system that receives list of organizations from experts,
mines their web corpus, prepare discourse topic lists with expert support, and then
ranks them on scales with partial expert interaction, and finally presents them on an
easy to use web based analytic system. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2016
| Identifer | oai:union.ndltd.org:asu.edu/item:39419 |
| Date | January 2016 |
| Contributors | Tikves, Sukru (Author), Davulcu, Hasan (Advisor), Sen, Arunabha (Committee member), Liu, Huan (Committee member), Woodward, Mark (Committee member), Arizona State University (Publisher) |
| Source Sets | Arizona State University |
| Language | English |
| Detected Language | English |
| Type | Doctoral Dissertation |
| Format | 73 pages |
| Rights | http://rightsstatements.org/vocab/InC/1.0/, All Rights Reserved |
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