Julia Silge
Impact in
- General Social Sciences top 0.5%
- Computational and Text Analysis Methods
- Communication top 5%
- Social Media and Politics
Papers in
-
- Galaxies: Formation, Evolution, Phenomena 2
- Stellar, planetary, and galactic studies 2
- Gamma-ray bursts and supernovae 1
-
- Advanced Text Analysis Techniques 2
- Data Analysis with R 1
- Sentiment Analysis and Opinion Mining 1
- Co-authors
- David M. Robinson (2 shared papers)David J. Robinson (2 shared papers)Karl Gebhardt (2 shared papers)Marcel Bergmann (1 shared paper)D. O. Richstone (1 shared paper)John C. Nash (1 shared paper)Jim Hester (1 shared paper)Spencer Graves (1 shared paper)
- Journals
- The Astronomical Journal (2 papers)The R Journal (1 paper)CERN Document Server (European Organization for Nuclear Research) (1 paper)The Journal of Open Source Software (1 paper)INFM-OAR (INFN Catania) (1 paper)
- Partner nations
- United StatesAustria
In The Last Decade
Julia Silge
6 papers receiving 928 citations
Julia Silge's Hit Papers
Peers
Comparison fields: 5 of 167
- General Social Sciences 87
- Communication 88
- Sociology and Political Science 259
- Artificial Intelligence 189
- Instrumentation 20
Countries citing papers authored by Julia Silge
This map shows the geographic impact of Julia Silge's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Julia Silge with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Julia Silge more than expected).
Fields of papers citing papers by Julia Silge
This network shows the impact of papers produced by Julia Silge. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Julia Silge. The network helps show where Julia Silge may publish in the future.
Co-authors
The 8 scholars most cited alongside Julia Silge, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | tidytext: Text Mining and Analysis Using Tidy Data Principles in R Hit paper breakdown → | 2016 | 561 |
| 2 | Text Mining with R: A Tidy Approach Hit paper breakdown → | 2017 | 326 |
| 3 | 2005 | 41 | |
| 4 | 2021 | 35 | |
| 5 | 2003 | 19 | |
| 6 | 2016 | 1 | |
| 7 | 2019 | 1 | |
| 8 | Weighted Tidy Log Odds Ratio [R package tidylo version 0.1.0] | 2020 | 1 |
| 9 | Text Mining using 'dplyr', 'ggplot2', and Other Tidy Tools [R package tidytext version 0.3.1] | 2021 | 0 |
About Julia Silge
Julia Silge is a scholar working on Astronomy and Astrophysics, Artificial Intelligence, Information Systems, Instrumentation and General Social Sciences, having authored 9 papers that have together received 985 indexed citations. Recurring topics across this work include Advanced Text Analysis Techniques (2 papers), Galaxies: Formation, Evolution, Phenomena (2 papers), Stellar, planetary, and galactic studies (2 papers), Data Analysis with R (1 paper), Astronomy and Astrophysical Research (1 paper), Sentiment Analysis and Opinion Mining (1 paper), Gamma-ray bursts and supernovae (1 paper) and Computational and Text Analysis Methods (1 paper). The work is most often cited by research in General Social Sciences (87 citations), Communication (88 citations), Sociology and Political Science (259 citations), Artificial Intelligence (189 citations) and Instrumentation (20 citations). Julia Silge has collaborated with scholars based in United States and Austria. Frequent co-authors include David M. Robinson, David J. Robinson, Karl Gebhardt, Marcel Bergmann, D. O. Richstone, John C. Nash, Jim Hester and Spencer Graves. Their work appears in journals such as The Astronomical Journal, The R Journal, CERN Document Server (European Organization for Nuclear Research), The Journal of Open Source Software and INFM-OAR (INFN Catania).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.