Hawkes binomial topic model with applications to coupled conflict-Twitter data
Autor: | George Mohler, Cody Buntain, Gary LaFree, Erin McGrath |
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Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
Statistics and Probability
Topic model Computer science social media dynamic topic model Dynamic topic model Binomial distribution Bag-of-words model Modeling and Simulation Econometrics Grievance Social media elections Statistics Probability and Uncertainty Hawkes process Branching process Event (probability theory) |
Zdroj: | Ann. Appl. Stat. 14, no. 4 (2020), 1984-2002 |
Popis: | We consider the problem of modeling and clustering heterogeneous event data arising from coupled conflict event and social media data sets. In this setting conflict events trigger responses on social media, and, at the same time, signals of grievance detected in social media may serve as leading indicators for subsequent conflict events. For this purpose we introduce the Hawkes Binomial Topic Model (HBTM) where marks, Tweets and conflict event descriptions are represented as bags of words following a Binomial distribution. When viewed as a branching process, the daughter event bag of words is generated by randomly turning on/off parent words through independent Bernoulli random variables. We then use expectation–maximization to estimate the model parameters and branching structure of the process. The inferred branching structure is then used for topic cascade detection, short-term forecasting, and investigating the causal dependence of grievance on social media and conflict events in recent elections in Nigeria and Kenya. |
Databáze: | OpenAIRE |
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