In this research, given a mixed set of senators/blogs debating on a set of political issues from opposing camps, I use signed bipartite graphs for modeling debates, and I propose an algorithm for partitioning both the opinion holders (senators or blogs) and the issues (bills or topics) comprising the debate into binary opposing camps. Simultaneously, my algorithm scales the entities on a univariate scale. Using this scale, a researcher can identify moderate and extreme senators/blogs within each camp, and polarizing versus unifying issues. Through performance evaluations I show that my proposed algorithm provides an effective solution to the problem, and performs much better than existing baseline algorithms adapted to solve this new problem. In my experiments, I used both real data from political blogosphere and US Congress records, as well as synthetic data which were obtained by varying polarization and degree distribution of the vertices of the graph to show the robustness of my algorithm.
I also applied my algorithm on all the terms of the US Senate to the date for longitudinal analysis and developed a web based interactive user interface www.PartisanScale.com to visualize the analysis.
US politics is most often polarized with respect to the left/right alignment of the entities. However, certain issues do not reflect the polarization due to political parties, but observe a split correlating to the demographics of the senators, or simply receive consensus. I propose a hierarchical clustering algorithm that identifies groups of bills that share the same polarization characteristics. I developed a web based interactive user interface www.ControversyAnalysis.com to visualize the clusters while providing a synopsis through distribution charts, word clouds, and heat maps.
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.
Religion in society has been a complex study for both academic and non-academic disciplines. Defining religion had become an issue since the beginning of world religions. This issue will continue to remain in society, unless world religions avoid imposed definition of religion from the world religions’ perspective. This research aims to study about how religion had been defined by many scholars theologically, politically, culturally, contextually, and how such different approaches never reach the consensus of understanding toward defining religion. In many cases, the definition of religion was imposed by scholars who have power of knowledge and intellectual in the discipline of world religions. The power of defining religion from the world religions’ perspective becomes challenging for people, such as indigenous people who continue to practice their religion from the origin of their fore-parents until today. Religion defined by world religions from the transcendental perspective had led to discrimination against other indigenous religions in various parts of the world, such as the Naga people in India.