Discovering themes and trends in transportation research using topic modeling. (April 2017)
- Record Type:
- Journal Article
- Title:
- Discovering themes and trends in transportation research using topic modeling. (April 2017)
- Main Title:
- Discovering themes and trends in transportation research using topic modeling
- Authors:
- Sun, Lijun
Yin, Yafeng - Abstract:
- Highlights: Applied the LDA model to discover transportation research themes from 17163 journal articles. Quantified general patterns of research topics at the level of journal, year, and country/region. The results could benefit different parties in transportation research community. Abstract: Transportation research is a key area in both science and engineering. In this paper, we present an empirical analysis of 17, 163 articles published in 22 leading transportation journals from 1990 to 2015. We apply a latent Dirichlet allocation (LDA) model on article abstracts to infer 50 key topics. We show that those characterized topics are both representative and meaningful, mostly corresponding to established sub-fields in transportation research. These identified fields reveal a research landscape for transportation. Based on the results of LDA, we quantify the similarity of journals and countries/regions in terms of their aggregated topic distributions. By measuring the variation of topic distributions over time, we find some general research trends, such as topics on sustainability, travel behavior and non-motorized mobility are becoming increasingly popular over time. We also carry out this temporal analysis for each journal, observing a high degree of consistency for most journals. However, some interesting anomaly, such as special issues on particular topics, are detected from temporal variation as well. By quantifying the temporal trends at the country/region level, weHighlights: Applied the LDA model to discover transportation research themes from 17163 journal articles. Quantified general patterns of research topics at the level of journal, year, and country/region. The results could benefit different parties in transportation research community. Abstract: Transportation research is a key area in both science and engineering. In this paper, we present an empirical analysis of 17, 163 articles published in 22 leading transportation journals from 1990 to 2015. We apply a latent Dirichlet allocation (LDA) model on article abstracts to infer 50 key topics. We show that those characterized topics are both representative and meaningful, mostly corresponding to established sub-fields in transportation research. These identified fields reveal a research landscape for transportation. Based on the results of LDA, we quantify the similarity of journals and countries/regions in terms of their aggregated topic distributions. By measuring the variation of topic distributions over time, we find some general research trends, such as topics on sustainability, travel behavior and non-motorized mobility are becoming increasingly popular over time. We also carry out this temporal analysis for each journal, observing a high degree of consistency for most journals. However, some interesting anomaly, such as special issues on particular topics, are detected from temporal variation as well. By quantifying the temporal trends at the country/region level, we find that countries/regions display clearly distinguishable patterns, suggesting that research communities in different regions tend to focus on different sub-fields. Our results could benefit different parties in the academic community—including researchers, journal editors and funding agencies—in terms of identifying promising research topics/projects, seeking for candidate journals for a submission, and realigning focus for journal development. … (more)
- Is Part Of:
- Transportation research. Volume 77(2017)
- Journal:
- Transportation research
- Issue:
- Volume 77(2017)
- Issue Display:
- Volume 77, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 77
- Issue:
- 2017
- Issue Sort Value:
- 2017-0077-2017-0000
- Page Start:
- 49
- Page End:
- 66
- Publication Date:
- 2017-04
- Subjects:
- Transportation research -- Topic modeling -- Publication data -- Research policy
Transportation -- Periodicals
Transportation -- Technological innovations -- Periodicals
388.011 - Journal URLs:
- http://www.sciencedirect.com/science/journal/0968090X ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.trc.2017.01.013 ↗
- Languages:
- English
- ISSNs:
- 0968-090X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9026.274620
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 2545.xml