zh:notes:education
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zh:notes:education [2022/12/21 09:29] pzczxs [Topic Discovery] |
zh:notes:education [2024/06/24 10:05] (当前版本) pzczxs [Extract Simple Cycles] |
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| ====== Mapping Technological Trajectories in the Education Domain ====== | ====== Mapping Technological Trajectories in the Education Domain ====== | ||
| ===== Citation Information ===== | ===== Citation Information ===== | ||
| - | To be added later. | + | -Shuo Xu, Congcong Wang, Xin An, Liyuan Hao, and Guancan Yang, 2024. [[https://doi.org/10.1177/01655515221101835|A Novel Developmental Trajectory Discovery Approach by Integrating Main Path Analysis and Intermediacy]]. //Journal of Information Science//, Vol. 50, No. 3, pp. 651-672. |
| + | - | ||
| ===== Requirements ===== | ===== Requirements ===== | ||
| *[[zh:notes:install_dtm|DTM]] | *[[zh:notes:install_dtm|DTM]] | ||
| + | *[[http://mrvar.fdv.uni-lj.si/pajek/|Pajek]] | ||
| ===== Dataset ===== | ===== Dataset ===== | ||
| The dataset comes form the following journals in the Web of Science (WoS). Here, we include all publications of the document type //Article//, //Article; Early Access//, //Article; Proceedings Paper//, //Database Review//, //Reprint//, and //Review// published before 2020 (inclusive). | The dataset comes form the following journals in the Web of Science (WoS). Here, we include all publications of the document type //Article//, //Article; Early Access//, //Article; Proceedings Paper//, //Database Review//, //Reprint//, and //Review// published before 2020 (inclusive). | ||
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| <code sql> | <code sql> | ||
| > SELECT ta_ca.target_article_id AS target_artice_id, ca.wos_id AS cited_article_id FROM target_article as ta, target_article_cited_article AS ta_ca, cited_article AS ca WHERE ta.id = ta_ca.target_article_id AND ta_ca.cited_article_id = ca.id AND ca.wos_id IS NOT NULL AND ta.publication_year <= 2020 And ta.publication_year != 0 AND ta.type IN ("Article; Proceedings Paper", "Reprint", "Article; Early Access", "Article", "Review", "Database Review") ORDER by ta_ca.target_article_id ASC; | > SELECT ta_ca.target_article_id AS target_artice_id, ca.wos_id AS cited_article_id FROM target_article as ta, target_article_cited_article AS ta_ca, cited_article AS ca WHERE ta.id = ta_ca.target_article_id AND ta_ca.cited_article_id = ca.id AND ca.wos_id IS NOT NULL AND ta.publication_year <= 2020 And ta.publication_year != 0 AND ta.type IN ("Article; Proceedings Paper", "Reprint", "Article; Early Access", "Article", "Review", "Database Review") ORDER by ta_ca.target_article_id ASC; | ||
| + | </code> | ||
| + | |||
| + | education technology: | ||
| + | <code sql> | ||
| + | > INSERT INTO citation (citing_doi, citing_publication_year, cited_doi, cited_publication_year) | ||
| + | > SELECT a.doi AS citing_doi, a.publication_year as citing_year, ca.doi AS cited_doi, ca.publication_year AS cited_year FROM article AS a, article_cited_article AS a_ca, cited_article AS ca | ||
| + | > WHERE a.id = a_ca.article_id AND a_ca.cited_article_id = ca.id | ||
| + | > AND a.TYPE IN ("Article", "Article; Early Access", "Article; Proceedings Paper", "Database Review", "Reprint", "Review", "Review; Early Access") | ||
| + | > AND a.doi is not null and ca.doi IS NOT NULL AND flag = 0 | ||
| + | > AND ca.journal_id IS NOT NULL | ||
| + | > ORDER BY citing_doi ASC, cited_doi ASC; | ||
| + | |||
| + | > DELETE FROM citation WHERE citing_doi = cited_doi; | ||
| </code> | </code> | ||
| 行 246: | 行 260: | ||
| For the sake of identifying a proper number of topics, the perplexity is calculated for each $K \in \{5, 10, \cdots, 50\}$ by running <color red>DTMTuningParam.java</color> in the package <color red>cn.edu.bjut.dtm</color>. In the end, $K$ is fixed to 30 in our case. | For the sake of identifying a proper number of topics, the perplexity is calculated for each $K \in \{5, 10, \cdots, 50\}$ by running <color red>DTMTuningParam.java</color> in the package <color red>cn.edu.bjut.dtm</color>. In the end, $K$ is fixed to 30 in our case. | ||
| - | Then, one can output top words for each topic and topic distribution for each document by running <color red>DTMPrinter.java</color> in the package <color red>cn.edu.bjut.dtm</color>. | + | Then, one can output top words for each topic and topic distribution for each document by running <color red>DTMPrinter.java</color> in the package <color red>cn.edu.bjut.dtm</color>. In this time, two files (//Education.twords// and //Education.vartheta//) will be generated. |
| ===== Main Path Analysis ===== | ===== Main Path Analysis ===== | ||
zh/notes/education.1671586162.txt.gz · 最后更改: 2022/12/21 09:29 由 pzczxs