Replication Data for: Modeling Conflict. Representations of Social Groups in Present-Day Dutch Literary Fiction. (doi:10.7910/DVN/JSKPQV)

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Part 1: Document Description
Part 2: Study Description
Part 3: Data Files Description
Part 4: Variable Description
Part 5: Other Study-Related Materials
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Document Description

Citation

Title:

Replication Data for: Modeling Conflict. Representations of Social Groups in Present-Day Dutch Literary Fiction.

Identification Number:

doi:10.7910/DVN/JSKPQV

Distributor:

Harvard Dataverse

Date of Distribution:

2021-06-09

Version:

1

Bibliographic Citation:

Smeets, Roel, 2021, "Replication Data for: Modeling Conflict. Representations of Social Groups in Present-Day Dutch Literary Fiction.", https://doi.org/10.7910/DVN/JSKPQV, Harvard Dataverse, V1, UNF:6:4wMaoJSDvCyJs9cRm06pXQ== [fileUNF]

Study Description

Citation

Title:

Replication Data for: Modeling Conflict. Representations of Social Groups in Present-Day Dutch Literary Fiction.

Identification Number:

doi:10.7910/DVN/JSKPQV

Authoring Entity:

Smeets, Roel (Radboud University Nijmegen)

Distributor:

Harvard Dataverse

Access Authority:

Smeets, Roel

Depositor:

Smeets, Roel

Date of Deposit:

2021-06-07

Holdings Information:

https://doi.org/10.7910/DVN/JSKPQV

Study Scope

Keywords:

Arts and Humanities, social network analysis, Dutch literature

Abstract:

Object-Oriented model written in Python, with three main classes: Character, Book, Network. Four interlinked databases: BOOKS_complete.csv contains all info on 170 contemporary Dutch novels NODES_complete.csv contains all demographic info on 2137 characters in those novels NAMES_complete.csv contains all name variants of those characters EDGES_complete.csv contains all relational info between those characters Python scripts: characternetworks.py contains the three classes Character, Book, and Network Superscript.py computes character networks, ranks all characters, and output the results to character-rankings.csv conflict.py models enemy/friend relations between characters on two levels: enemy/friend triads: tests Heider's social balance theory based on enemies and friends in the corpus enemy dyads: computes hierarchies between every two enemies based on a 'conflictscore' (one for each measure) Csv output: - character-rankings.csv (output of write_to_csv() in Superscript.py) - character-rankings_conflictscore.csv (output of conflict.py) The text-files of the 170 novels from 2012 cannot be shared due to copyright.

Methodology and Processing

Sources Statement

Data Access

Notes:

<a href="http://creativecommons.org/publicdomain/zero/1.0">CC0 1.0</a>

Other Study Description Materials

File Description--f4786731

File: BOOKS_complete.tab

  • Number of cases: 170

  • No. of variables per record: 8

  • Type of File: text/tab-separated-values

Notes:

UNF:6:nP68eDZnxxjI6VbSbI86Eg==

File Description--f4786728

File: EDGES_complete.tab

  • Number of cases: 8775

  • No. of variables per record: 4

  • Type of File: text/tab-separated-values

Notes:

UNF:6:iRfSft3mvo4AX3T+Q/cuJw==

File Description--f4786729

File: NODES_complete.tab

  • Number of cases: 2137

  • No. of variables per record: 1

  • Type of File: text/tab-separated-values

Notes:

UNF:6:Cv9kjry32AgWlnl5gAMN/A==

Variable Description

List of Variables:

Variables

book_id

f4786731 Location:

Summary Statistics: Mean 85.5; Valid 170.0; StDev 49.21889880929885; Min. 1.0; Max. 170.0

Variable Format: numeric

Notes: UNF:6:OBo2AblBuqPBvpNdR/HJCA==

title

f4786731 Location:

Variable Format: character

Notes: UNF:6:+qGIokZkxDXNnMw4d/9btw==

name_author

f4786731 Location:

Variable Format: character

Notes: UNF:6:P1SmULnRtMgZBw7A+LTz2w==

gender_author

f4786731 Location:

Variable Format: character

Notes: UNF:6:BoVIQHS9VJw5MQkJXkbGFQ==

age_author

f4786731 Location:

Variable Format: character

Notes: UNF:6:XUWNWus5640xhnk41oQvHg==

publisher

f4786731 Location:

Variable Format: character

Notes: UNF:6:AhbmtSjWcAf5e1+644nMkQ==

perspective

f4786731 Location:

Summary Statistics: Mean 1.7705882352941176; Max. 3.0; Min. 1.0; StDev 0.7617052699069164; Valid 170.0

Variable Format: numeric

Notes: UNF:6:Y2OeSx3j0nhiRS5OF1xdFA==

filename

f4786731 Location:

Variable Format: character

Notes: UNF:6:ijZ0X3cP6wDzsQvuDde9Xg==

book_id

f4786728 Location:

Summary Statistics: Valid 8775.0; Min. 1.0; StDev 48.738354578131236; Mean 95.66518518519054; Max. 170.0;

Variable Format: numeric

Notes: UNF:6:G6rN8qqtyJYv4Yp01625kg==

source

f4786728 Location:

Summary Statistics: Mean 7.065754985754907; Valid 8775.0; Max. 29.0; StDev 5.736989218210115; Min. 1.0

Variable Format: numeric

Notes: UNF:6:RZEBrO6oR4cUemCvxF1CEw==

target

f4786728 Location:

Summary Statistics: Max. 29.0; StDev 5.710426507500926; Valid 8775.0; Mean 7.036809116809002; Min. 1.0;

Variable Format: numeric

Notes: UNF:6:pm9IK15JLkkMzfeVr93shg==

relation_type

f4786728 Location:

Variable Format: character

Notes: UNF:6:WSlhx3BuEYyK3gbga6piMQ==

book_id;character_id;name;gender;descent_country;descent_city;living_country;living_city;age;education;profession

f4786729 Location:

Variable Format: character

Notes: UNF:6:Cv9kjry32AgWlnl5gAMN/A==

Other Study-Related Materials

Label:

character-rankings.csv

Notes:

text/csv

Other Study-Related Materials

Label:

character-rankings_conflictscore.csv

Notes:

text/csv

Other Study-Related Materials

Label:

characternetworks.py

Notes:

text/x-python-script

Other Study-Related Materials

Label:

conflict.py

Notes:

text/x-python-script

Other Study-Related Materials

Label:

NAMES_complete.csv

Notes:

text/csv

Other Study-Related Materials

Label:

Superscript.py

Notes:

text/x-python-script