Assessing Sentiment in Conflict Zones Through Social Media: Case Study of Yemen Shows That Social Media Data Can be Combined with Polling to Determine Levels of Support for Government and Extremists

by Progressive Management
$8.55
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Publisher: Progressive Management

Publication Date: April 25, 2019

ISBN: 9780463483046

Binding: Kobo eBook

Availability: eBook

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This report has been professionally converted for accurate flowing-text e-book format reproduction. While it is widely accepted that polling can assess levels of popular support in a geographic area by surveying a cross-segment of its population, it is less well accepted that analysts can use social media analysis to assess sentiment or popular support within the same space. We examine this question by comparing geographically anchored polling and social media data, utilizing over 1.4 million geo-referenced messages sent through the Twitter network from Yemen over the period from October 2013 to January 2014, to assess both support for extremist groups and support to the Yemeni government. From our research, we conclude that social media data, when combined with polling, has a positive impact on analysis. It can also be a reliable source of stand-alone data for evaluating popular support under certain conditions. Therefore, we recommend future research projects focus on improving the quality of social media data and on operational changes to improve the integration of social media analysis into assessment plans.

This compilation includes a reproduction of the 2019 Worldwide Threat Assessment of the U.S. Intelligence Community.

I. Introduction * II. Literature Review * A. Military Doctrine and Assessment * B. Social Media Analysis * III. Background—Yemen * A. Violent Extremist Organizations * B. Houthis * C. Salafis * D. Al-Qaeda in the Arabian Peninsula and Yemen * E. Government of Yemen * IV. Research Methods * A. Hypothesis * B. Data and Methods * 1. Social Media * 2. Sentiment Dictionary * 3. Kernel Density Estimates * 4. Dependent Variables * 5. Independent Variables * 6. Control Variables * C. Regression Analysis * V. Results * A. Finding One - Improves Predictions * B. Finding Two - Similarity of Spatial Patterns * C. Finding Three - Sentiment Matters * D. Finding Four - The Importance of the Topic * E.