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題名 南海緊張情勢：GDELT 時間序列數據之分析
South China Sea Tensions : State Involvement and Prediction Using GDELT Event Data
作者 錫東岳
Spangler, Jonathan
貢獻者 劉復國
Liu, Fu-Kuo
錫東岳
Jonathan Spangler
關鍵詞 事件數據
GDELT
GKG
海域爭端
南海
國家介入
緊張情勢
時間序列
Event data
GDELT
GKG
Maritime territorial disputes
South China Sea
State involvement
Tensions
Time series
日期 2018
上傳時間 9-Apr-2018 16:05:31 (UTC+8)
摘要 無
Discussions of the South China Sea maritime territorial disputes are rife with assertions that certain state actors escalate regional tensions and that it is only a matter of time before provocations trigger armed conflict. However, these claims are based primarily on incomplete evidence, inaccurate comparisons with historical conflicts, and country or individual biases. This dissertation questions these common assertions and uses empirical evidence to assess their validity. Using time-series event data from the Global Database of Events, Language, and Tone (GDELT), it analyzes (1) the relationship between state involvement and South China Sea tensions and (2) which forecast models can most accurately predict South China Sea tensions based on data from earlier time periods.
For RQ1, the analyses reveal that the involvement of certain countries corresponds with significantly higher tensions in the South China Sea, that state involvement and tensions are correlated at various positive and negative lags of interest, and that these correlations go in both directions. These findings have important implications for policymakers and researchers in that they offer empirical evidence that confirms or refutes assertions suggesting that certain countries’ actions lead to escalation or deescalation. They also provide a solid foundation for future research, which could take specific countries as individual case studies to further investigate the relationships between state involvement and South China Sea tensions. Moreover, the results indicate that there may be even more interesting phenomena at play that merit attention in future research: evidence suggesting that certain countries may either contribute to lower tensions or avoid becoming involved when there are heightened tensions, and evidence that some countries may not be contributing to but instead reacting to tensions and volatility in the South China Sea.
For RQ2, two of the four forecast models perform better than the four benchmark models using both datasets. These findings also have important implications for policy and research. As governments become increasingly interested in using continuously updated global databases to facilitate policy-making, the results suggest that empirical data can help to inform conclusions about trends of escalation and deescalation in the South China Sea and be used to make relevant predictions. As a first cut at the data and a pioneering approach to analyzing South China Sea tensions, the analyses and findings of this dissertation represent a significant contribution to knowledge and a foundation for future research using time-series event data to understand the relationship between state involvement and tensions and the extent to which tensions can be forecasted in the South China Sea and around the world.
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描述 博士
國立政治大學
亞太研究英語博士學位學程(IDAS)
101265507
資料來源 http://thesis.lib.nccu.edu.tw/record/#G1012655072
資料類型 thesis
dc.contributor.advisor 劉復國zh_TW
dc.contributor.advisor Liu, Fu-Kuoen_US
dc.contributor.author (Authors) 錫東岳zh_TW
dc.contributor.author (Authors) Jonathan Spangleren_US
dc.creator (作者) 錫東岳zh_TW
dc.creator (作者) Spangler, Jonathanen_US
dc.date (日期) 2018en_US
dc.date.accessioned 9-Apr-2018 16:05:31 (UTC+8)-
dc.date.available 9-Apr-2018 16:05:31 (UTC+8)-
dc.date.issued (上傳時間) 9-Apr-2018 16:05:31 (UTC+8)-
dc.identifier (Other Identifiers) G1012655072en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/116793-
dc.description (描述) 博士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 亞太研究英語博士學位學程(IDAS)zh_TW
dc.description (描述) 101265507zh_TW
dc.description.abstract (摘要) 無zh_TW
dc.description.abstract (摘要) Discussions of the South China Sea maritime territorial disputes are rife with assertions that certain state actors escalate regional tensions and that it is only a matter of time before provocations trigger armed conflict. However, these claims are based primarily on incomplete evidence, inaccurate comparisons with historical conflicts, and country or individual biases. This dissertation questions these common assertions and uses empirical evidence to assess their validity. Using time-series event data from the Global Database of Events, Language, and Tone (GDELT), it analyzes (1) the relationship between state involvement and South China Sea tensions and (2) which forecast models can most accurately predict South China Sea tensions based on data from earlier time periods.
For RQ1, the analyses reveal that the involvement of certain countries corresponds with significantly higher tensions in the South China Sea, that state involvement and tensions are correlated at various positive and negative lags of interest, and that these correlations go in both directions. These findings have important implications for policymakers and researchers in that they offer empirical evidence that confirms or refutes assertions suggesting that certain countries’ actions lead to escalation or deescalation. They also provide a solid foundation for future research, which could take specific countries as individual case studies to further investigate the relationships between state involvement and South China Sea tensions. Moreover, the results indicate that there may be even more interesting phenomena at play that merit attention in future research: evidence suggesting that certain countries may either contribute to lower tensions or avoid becoming involved when there are heightened tensions, and evidence that some countries may not be contributing to but instead reacting to tensions and volatility in the South China Sea.
For RQ2, two of the four forecast models perform better than the four benchmark models using both datasets. These findings also have important implications for policy and research. As governments become increasingly interested in using continuously updated global databases to facilitate policy-making, the results suggest that empirical data can help to inform conclusions about trends of escalation and deescalation in the South China Sea and be used to make relevant predictions. As a first cut at the data and a pioneering approach to analyzing South China Sea tensions, the analyses and findings of this dissertation represent a significant contribution to knowledge and a foundation for future research using time-series event data to understand the relationship between state involvement and tensions and the extent to which tensions can be forecasted in the South China Sea and around the world.		en_US
dc.description.tableofcontents Abstract 1
Acknowledgements 3
Table of Contents 5
List of Tables 9
List of Figures 11
List of Abbreviations 15
1. Introduction 17
1.1 Background 17
1.2 Significance of the Study 17
1.3 Research Questions 19
1.3.1 RQ1: State Involvement and Tensions 19
1.3.2 RQ2: Predicting Tensions 19
2. Literature Review 21
2.1 Context of the South China Sea Disputes 21
2.2 Effects of State Involvement on Tensions 25
2.2.1 China’s Involvement and Tensions 26
2.2.2 US Involvement and Tensions 29
2.2.3 Other Rival Claimants’ Involvement and Tensions 33
2.2.4 Other Major Stakeholders’ Involvement and Tensions 35
2.2.5 Ambiguous Statements Linking State Involvement and Tensions 37
2.2.6 Empirical Evidence and the Relationship between State Involvement and Tensions 39
2.2.7 Theoretical Framework for RQ1 40
2.3 Predicting Tensions and Conflict 42
2.3.1 Academic Predictions of Tensions and Conflict 43
2.3.2 Policymaker Predictions of Tensions and Conflict 46
2.3.3 Media Predictions of Tensions and Conflict 48
2.3.4 Empirical Evidence and Predictions of Tensions and Conflict 49
2.3.5 Theoretical Framework for RQ2 51
2.4 Modeling Real World Processes 53
2.5 Analyses with GDELT in Other Geographic Contexts 54
2.6 Defining Relevant Terms 60
3. Methodology 63
3.1 Data Sources 64
3.1.1 Global Database of Events, Language, and Tone (GDELT) 64
3.1.2 GDELT 1.0 Event Database 65
3.1.3 GDELT 2.0 Global Knowledge Graph (GKG) 66
3.1.4 Database Comparison 67
3.2 Data Selection 68
3.2.1 Tensions Data Selection from GDELT 1.0 Event Database 69
3.2.2 Linking GDELT 1.0 Event Database Data to Real-World Events 73
3.2.3 State Involvement Data Selection from GDELT 1.0 Event Database for RQ1 78
3.2.4 Tensions Data Selection from GDELT 2.0 GKG 79
3.2.5 Linking GDELT 2.0 GKG Data to Real-World Events 83
3.2.6 State Involvement Data Selection from GDELT 2.0 GKG for RQ1 86
3.2.7 Tensions Data Selection for RQ2 88
3.2.8 Comparing Datasets 89
3.3 Statistical Approach for RQ1 90
3.3.1 Observed Data 91
3.3.2 Difference Analyses 104
3.3.3 Cross-Correlation Analyses 106
3.3.4 Hypotheses for RQ1 107
3.4 Statistical Approach for RQ2 108
3.4.1 Observed Data 109
3.4.2 Training Data and Test Data 110
3.4.3 Benchmark Models 111
3.4.4 Forecast Models 120
3.4.5 Summary of Models 131
3.4.7 Comparison of Forecast Errors 132
3.4.8 Hypotheses for RQ2 133
3.5 Limitations 133
3.5.1 Proxy Variables 134
3.5.2 Data Availability 134
3.5.3 Definitions of State Involvement and South China Sea 135
3.5.4 Correlation and Causation 135
4. Results and Discussion 137
4.1 State Involvement and Tensions 138
4.1.1 Difference Analyses 139
4.1.2 Cross-Correlation Analyses 154
4.1.3 Evaluation of Hypotheses for RQ1 165
4.2 Predicting Tensions 166
4.2.1 Benchmark Models 167
4.2.2 Forecast Models 176
4.2.3 Model Comparison 187
4.2.4 Evaluation of Hypotheses for RQ2 189
4.3 Further Discoveries 190
4.3.1 Trends of Escalation and Deescalation 191
4.3.2 Changes in State Involvement 192
4.3.3 Reacting to Tensions 194
5. Conclusion 197
5.1 State Involvement and Tensions 197
5.1.1 Summary of Findings 197
5.1.2 Implications, Policy Recommendations, and Future Research 199
5.2 Predicting Tensions 201
5.2.1 Summary of Findings 201
5.2.2 Implications, Policy Recommendations, and Future Research 202
5.3 Further Discoveries 203
5.3.1 Summary of Findings 203
5.3.2 Implications, Policy Recommendations, and Future Research 205
Bibliography 207
Appendix I: GDELT Data Selection Code for Google BigQuery 225
Appendix II: GDELT Data Analysis Code for R 249
Appendix III: Codebook Excerpts 331		zh_TW
dc.format.extent 5536571 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G1012655072en_US
dc.subject (關鍵詞) 事件數據zh_TW
dc.subject (關鍵詞) GDELTzh_TW
dc.subject (關鍵詞) GKGzh_TW
dc.subject (關鍵詞) 海域爭端zh_TW
dc.subject (關鍵詞) 南海zh_TW
dc.subject (關鍵詞) 國家介入zh_TW
dc.subject (關鍵詞) 緊張情勢zh_TW
dc.subject (關鍵詞) 時間序列zh_TW
dc.subject (關鍵詞) Event dataen_US
dc.subject (關鍵詞) GDELTen_US
dc.subject (關鍵詞) GKGen_US
dc.subject (關鍵詞) Maritime territorial disputesen_US
dc.subject (關鍵詞) South China Seaen_US
dc.subject (關鍵詞) State involvementen_US
dc.subject (關鍵詞) Tensionsen_US
dc.subject (關鍵詞) Time seriesen_US
dc.title (題名) 南海緊張情勢：GDELT 時間序列數據之分析zh_TW
dc.title (題名) South China Sea Tensions : State Involvement and Prediction Using GDELT Event Dataen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Official Documents and Reports
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Joshua S. Goldstein, “A Conflict-Cooperation Scale for WEIS Events Data,” Journal of Conflict Resolution 36(2): 369–385, June 1, 1992, pp. 376–377, .
Rob J. Hyndman and A. B. Koehler, “Another look at measures of forecast accuracy,” International Journal of Forecasting 22(4): 679–688, 2006.
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YingHui Lee, “Expanding CUES: Singapore’s timely proposal,” RSIS Commentaries 63, Nanyang Technological University, March 24, 2016, p. 2, .
Kalev Leetaru and Philip Schrodt, “GDELT: Global Data on Events, Language, and Tone, 1979-2012,” International Studies Association Annual Conference, San Diego, CA, April 2013, .
Steven I. Levine, “The China Fallacy: How the US Can Benefit from China’s Rise and Avoid Another Cold War,” Journal of Contemporary Asia, ahead-of-print, 1–3, 2013, p. 1, .
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News Articles, Analysis, and Commentary
Keith Bradsher, “China Is Said to Be Bolstering Missile Capabilities,” The New York Times, August 24, 2012, .
Rowan Callick, “Taiwan escalates contest of the seas,” The Australian, July 14, 2014, .
Jun Endo, “Duterte’s pivot to Beijing brings calm to South China Sea,” Nikkei Asian Review, November 9, 2016, .
Paterno Esmaquel II, “No mention of Hague ruling in ASEAN chairman’s statement,” Rappler, September 7, 2016, .
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Reference Material
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