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Part 1: Document Description
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Citation |
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Title: |
Replication Data for: Exponential Random Graph Models for Dynamic Signed Networks: An Application to International Politics |
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Identification Number: |
doi:10.7910/DVN/7ZRCS6 |
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Distributor: |
Harvard Dataverse |
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Date of Distribution: |
2024-10-09 |
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Version: |
1 |
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Bibliographic Citation: |
Fritz, Cornelius, 2024, "Replication Data for: Exponential Random Graph Models for Dynamic Signed Networks: An Application to International Politics", https://doi.org/10.7910/DVN/7ZRCS6, Harvard Dataverse, V1 |
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Citation |
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Title: |
Replication Data for: Exponential Random Graph Models for Dynamic Signed Networks: An Application to International Politics |
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Identification Number: |
doi:10.7910/DVN/7ZRCS6 |
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Authoring Entity: |
Fritz, Cornelius (Penn State University) |
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Producer: |
<i>Political Analysis</i> |
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Distributor: |
Harvard Dataverse |
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Access Authority: |
Fritz, Cornelius |
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Depositor: |
Fritz, Cornelius |
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Date of Deposit: |
2024-03-27 |
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Holdings Information: |
https://doi.org/10.7910/DVN/7ZRCS6 |
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Study Scope |
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Keywords: |
Social Sciences |
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Abstract: |
Substantive research in the Social Sciences regularly investigates signed networks, where edges between actors are positive or negative. One often-studied example within International Relations for this type of network consists of countries that can cooperate with or fight against each other. These analyses often build on structural balance theory, one of the earliest and most prominent network theories. While the theorization and description of signed networks have made significant progress, the inferential study of link formation within them remains limited in the absence of appropriate statistical models. We fill this gap by proposing the Signed Exponential Random Graph Model (SERGM), extending the well-known Exponential Random Graph Model (ERGM) to networks where ties are not binary but positive or negative if a tie exists. Since most networks are dynamically evolving systems, we specify the model for both cross-sectional and dynamic networks. Based on hypotheses derived from structural balance theory, we formulate interpretable signed network statistics, capturing dynamics such as "the enemy of my enemy is my friend". In our empirical application, we use the SERGM to analyze cooperation and conflict between countries within the international state system. We find evidence for structural balance in International Relations. |
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Methodology and Processing |
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Select one option from below, remove everything else: Forthcoming, Political Analysis OR If Print Published complete below, remove this note: Author first and last name. year. "study name." Political Analysis, Volume #, Issue #, Pages. <a href= "link to article" target= "_new">article available here</a> AND If your DOI# and article are available, include that information in the fields below labeled and remove this note before hitting SAVE: ID Type; ID Number, and URL. |
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Identification Number: |
add DOI# here when available. If not available, please delete all text in this field before saving |
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Bibliographic Citation: |
Select one option from below, remove everything else: Forthcoming, Political Analysis OR If Print Published complete below, remove this note: Author first and last name. year. "study name." Political Analysis, Volume #, Issue #, Pages. <a href= "link to article" target= "_new">article available here</a> AND If your DOI# and article are available, include that information in the fields below labeled and remove this note before hitting SAVE: ID Type; ID Number, and URL. |
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Label: |
README.md |
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Notes: |
text/markdown |
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Label: |
sergm_replication.zip |
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Notes: |
application/zip |