Artificial Intelligence for the Internal Democracy of Political Parties
The article argues that AI can enhance the measurement and implementation of democratic processes within political parties, known as Intra-Party Democracy (IPD). It identifies the limitations of traditional methods for measuring IPD, which often rely on formal parameters, self-reported data, and too...
| Main Authors: | , , , , |
|---|---|
| Format: | Journal article |
| Language: | English |
| Published: |
Springer
2024
|
| _version_ | 1811141179688878080 |
|---|---|
| author | Novelli, C Formisano, G Juneja, P Sandri, G Floridi, L |
| author_facet | Novelli, C Formisano, G Juneja, P Sandri, G Floridi, L |
| author_sort | Novelli, C |
| collection | OXFORD |
| description | The article argues that AI can enhance the measurement and implementation of democratic processes within political parties, known as Intra-Party Democracy (IPD). It identifies the limitations of traditional methods for measuring IPD, which often rely on formal parameters, self-reported data, and tools like surveys. Such limitations lead to partial data collection, rare updates, and significant resource demands. To address these issues, the article suggests that specific data management and Machine Learning techniques, such as natural language processing and sentiment analysis, can improve the measurement and practice of IPD. |
| first_indexed | 2024-09-25T04:33:46Z |
| format | Journal article |
| id | oxford-uuid:95f3de28-93bb-4b1c-b9ea-552fb8086608 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-09-25T04:33:46Z |
| publishDate | 2024 |
| publisher | Springer |
| record_format | dspace |
| spelling | oxford-uuid:95f3de28-93bb-4b1c-b9ea-552fb80866082024-09-04T20:07:40ZArtificial Intelligence for the Internal Democracy of Political PartiesJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:95f3de28-93bb-4b1c-b9ea-552fb8086608EnglishJisc Publications RouterSpringer2024Novelli, CFormisano, GJuneja, PSandri, GFloridi, LThe article argues that AI can enhance the measurement and implementation of democratic processes within political parties, known as Intra-Party Democracy (IPD). It identifies the limitations of traditional methods for measuring IPD, which often rely on formal parameters, self-reported data, and tools like surveys. Such limitations lead to partial data collection, rare updates, and significant resource demands. To address these issues, the article suggests that specific data management and Machine Learning techniques, such as natural language processing and sentiment analysis, can improve the measurement and practice of IPD. |
| spellingShingle | Novelli, C Formisano, G Juneja, P Sandri, G Floridi, L Artificial Intelligence for the Internal Democracy of Political Parties |
| title | Artificial Intelligence for the Internal Democracy of Political Parties |
| title_full | Artificial Intelligence for the Internal Democracy of Political Parties |
| title_fullStr | Artificial Intelligence for the Internal Democracy of Political Parties |
| title_full_unstemmed | Artificial Intelligence for the Internal Democracy of Political Parties |
| title_short | Artificial Intelligence for the Internal Democracy of Political Parties |
| title_sort | artificial intelligence for the internal democracy of political parties |
| work_keys_str_mv | AT novellic artificialintelligencefortheinternaldemocracyofpoliticalparties AT formisanog artificialintelligencefortheinternaldemocracyofpoliticalparties AT junejap artificialintelligencefortheinternaldemocracyofpoliticalparties AT sandrig artificialintelligencefortheinternaldemocracyofpoliticalparties AT floridil artificialintelligencefortheinternaldemocracyofpoliticalparties |