Daniel J. Liebling

746 total citations
14 papers, 516 citations indexed

About

Daniel J. Liebling is a scholar working on Information Systems, Artificial Intelligence and Human-Computer Interaction. According to data from OpenAlex, Daniel J. Liebling has authored 14 papers receiving a total of 516 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Information Systems, 4 papers in Artificial Intelligence and 3 papers in Human-Computer Interaction. Recurrent topics in Daniel J. Liebling's work include Web Data Mining and Analysis (4 papers), Information Retrieval and Search Behavior (4 papers) and Personal Information Management and User Behavior (2 papers). Daniel J. Liebling is often cited by papers focused on Web Data Mining and Analysis (4 papers), Information Retrieval and Search Behavior (4 papers) and Personal Information Management and User Behavior (2 papers). Daniel J. Liebling collaborates with scholars based in United States and United Kingdom. Daniel J. Liebling's co-authors include Jaime Teevan, Susan Dumais, Sören Preibusch, Eric Horvitz, Michael S. Bernstein, Walter S. Lasecki, Meredith Ringel Morris, Michal Lahav, Paul N. Bennett and Richard L. Hughes and has published in prestigious journals such as .

In The Last Decade

Daniel J. Liebling

14 papers receiving 481 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Daniel J. Liebling United States 11 300 172 95 85 83 14 516
Kumaripaba Athukorala Finland 11 262 0.9× 182 1.1× 39 0.4× 112 1.3× 75 0.9× 23 492
David Piorkowski United States 10 283 0.9× 136 0.8× 66 0.7× 69 0.8× 148 1.8× 22 480
Resa A. Roth United States 3 345 1.1× 216 1.3× 27 0.3× 120 1.4× 67 0.8× 3 552
Haowei Hsieh United States 13 252 0.8× 152 0.9× 150 1.6× 149 1.8× 66 0.8× 31 557
Daniel Alexander Smith United Kingdom 9 138 0.5× 153 0.9× 45 0.5× 120 1.4× 47 0.6× 26 391
Clemens Drews United States 11 166 0.6× 183 1.1× 99 1.0× 89 1.0× 59 0.7× 16 577
Mika Käki Finland 9 249 0.8× 94 0.5× 63 0.7× 47 0.6× 34 0.4× 13 359
Thomas White United States 6 321 1.1× 112 0.7× 18 0.2× 62 0.7× 66 0.8× 36 484
Joel Lewenstein United States 5 319 1.1× 85 0.5× 80 0.8× 39 0.5× 179 2.2× 5 472
Karl Gyllstrom United States 9 176 0.6× 64 0.4× 48 0.5× 37 0.4× 37 0.4× 23 275

Countries citing papers authored by Daniel J. Liebling

Since Specialization
Citations

This map shows the geographic impact of Daniel J. Liebling'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 Daniel J. Liebling with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel J. Liebling more than expected).

Fields of papers citing papers by Daniel J. Liebling

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel J. Liebling. 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 Daniel J. Liebling. The network helps show where Daniel J. Liebling may publish in the future.

Co-authorship network of co-authors of Daniel J. Liebling

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel J. Liebling. A scholar is included among the top collaborators of Daniel J. Liebling based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel J. Liebling. Daniel J. Liebling is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
Liebling, Daniel J., et al.. (2022). Opportunities for Human-centered Evaluation of Machine Translation Systems. 229–240. 4 indexed citations
2.
Liebling, Daniel J., Katherine Heller, Margaret Mitchell, et al.. (2021). Three Directions for the Design of Human-Centered Machine Translation. 4 indexed citations
3.
Liebling, Daniel J., et al.. (2020). Unmet Needs and Opportunities for Mobile Translation AI. 1–13. 28 indexed citations
4.
Liebling, Daniel J. & Susan Dumais. (2014). Gaze and mouse coordination in everyday work. 1141–1150. 37 indexed citations
5.
Liebling, Daniel J. & Sören Preibusch. (2014). Privacy considerations for a pervasive eye tracking world. 1169–1177. 42 indexed citations
6.
Teevan, Jaime, Daniel J. Liebling, & Walter S. Lasecki. (2014). Selfsourcing personal tasks. 2527–2532. 31 indexed citations
7.
Bernstein, Michael S., Jaime Teevan, Susan Dumais, Daniel J. Liebling, & Eric Horvitz. (2012). Direct answers for search queries in the long tail. 237–246. 68 indexed citations
8.
Liebling, Daniel J., Paul N. Bennett, & Ryen W. White. (2012). Anticipatory search. 1035–1036. 13 indexed citations
9.
Liebling, Daniel J. & Meredith Ringel Morris. (2012). Kinected browser. 105–108. 10 indexed citations
10.
Teevan, Jaime, et al.. (2012). Displaying mobile feedback during a presentation. 379–382. 11 indexed citations
11.
Teevan, Jaime, et al.. (2011). Understanding and predicting personal navigation. 85–94. 56 indexed citations
12.
Teevan, Jaime, Susan Dumais, & Daniel J. Liebling. (2010). A longitudinal study of how highlighting web content change affects people's web interactions. 1353–1356. 16 indexed citations
13.
Teevan, Jaime, Susan Dumais, Daniel J. Liebling, & Richard L. Hughes. (2009). Changing how people view changes on the web. 237–246. 17 indexed citations
14.
Teevan, Jaime, Susan Dumais, & Daniel J. Liebling. (2008). To personalize or not to personalize. 163–170. 179 indexed citations

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.

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