LaTeCH-CLfL-2020

与历史到神话：比较不同时期故事的社会网络分析论文相关的存储库。

引用

@inproceedings{besnier-2020-history,
    title = "History to Myths: Social Network Analysis for Comparison of Stories over Time",
    author = "Besnier, Cl{\'e}ment",
    booktitle = "Proceedings of the The 4th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature",
    month = dec,
    year = "2020",
    address = "Online",
    publisher = "International Committee on Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2020.latechclfl-1.1",
    pages = "1--9",
    abstract = {We discuss on how related stories can be compared by their characters. We investigate character graphs, or social networks, in order to measure evolution of character importance over time. To illustrate this, we chose the Siegfried-Sigurd myth that may come from a Merovingian king named Sigiberthus. The Nibelungenlied, the V{\"o}lsunga saga and the History of the Franks are the three resources used.},
}

数据

文本

• Decem libros historium (DLH) by Gregory of Tours
• Nibelungenlied (NIB)
• Völsunga saga (VOL)

DLH是历史参考。 NIB和 VÖL是虚构作品。

安装

在Windows 10和Ubuntu 16.04上测试。使用Python 3.7和3.8进行测试。

使用pip安装

$ pip install latechclfl2020besnier

或下载源代码

$ git clone https://github.com/clemsciences/LaTeCH-CLfl-2020-besnier.git
$ cd LaTeCH-CLfl-2020-besnier
$ virtualenv -p /usr/bin/python3 venv
$ source venv/bin/activate
$ pip install -r requirements.txt 

重现结果

1. 下载资源 运行 $ python -m -m latechclfl2020.models.initiate latechclfl2020/models/initiate.py
2. 生成图形。运行 $ python -m latechclfl2020.models.scripts latechclfl2020/models/scripts.py
3. 生成论文中的角色特征表。运行 $ python -m latechclfl2020.models.reconstruction latechclfl2020/models/reconstruction.py
4. 生成Brynhildr自我图。运行 $ python -m latechclfl2020.models.paper.graph_visualisation latechclfl2020/models/paper/graph_visualisation.py
5. 语料库观察。运行 $ python -m latechclfl2020.models.paper.corpus_observation latechclfl2020/models/paper/corpus_observation.py