Title | ||
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A Frame Of Mind: Using Statistical Models For Detection Of Framing And Agenda Setting Campaigns |
Abstract | ||
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Framing is a sophisticated form of discourse in which the speaker tries to induce a cognitive bias through consistent linkage between a topic and a specific context (frame). We build on political science and communication theory and use probabilistic topic models combined with time series regression analysis (autoregressive distributed-lag models) to gain insights about the language dynamics in the political processes. Processing four years of public statements issued by members of the U.S. Congress, our results provide a glimpse into the complex dynamic processes of framing, attention shifts and agenda setting, commonly known as 'spin'. We further provide new evidence for the divergence in party discipline in U.S. politics. |
Year | Venue | Field |
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2015 | PROCEEDINGS OF THE 53RD ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS AND THE 7TH INTERNATIONAL JOINT CONFERENCE ON NATURAL LANGUAGE PROCESSING, VOL 1 | Framing (construction),Cognitive bias,Time series,Computer science,Communication theory,Artificial intelligence,Statistical model,Natural language processing,Probabilistic logic,Topic model,Epistemology,Politics |
DocType | Volume | Citations |
Conference | P15-1 | 12 |
PageRank | References | Authors |
0.65 | 7 | 3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Oren Tsur | 1 | 568 | 29.83 |
Dan Calacci | 2 | 12 | 0.65 |
David Lazer | 3 | 42 | 5.17 |