Theodoros Lappas

2.5k total citations · 1 hit paper
49 papers, 1.6k citations indexed

About

Theodoros Lappas is a scholar working on Artificial Intelligence, Information Systems and Sociology and Political Science. According to data from OpenAlex, Theodoros Lappas has authored 49 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 12 papers in Information Systems and 11 papers in Sociology and Political Science. Recurrent topics in Theodoros Lappas's work include Digital Marketing and Social Media (10 papers), Complex Network Analysis Techniques (8 papers) and Sentiment Analysis and Opinion Mining (6 papers). Theodoros Lappas is often cited by papers focused on Digital Marketing and Social Media (10 papers), Complex Network Analysis Techniques (8 papers) and Sentiment Analysis and Opinion Mining (6 papers). Theodoros Lappas collaborates with scholars based in United States, Greece and Finland. Theodoros Lappas's co-authors include Evimaria Terzi, Kun Liu, Dimitrios Gunopulos, Gaurav Sabnis, Konstantinos Pelechrinis, Marios Kokkodis, Heikki Mannila, Panagiotis P. Repoussis, Aristides Gionis and Vassilis J. Tsotras and has published in prestigious journals such as PLoS ONE, Tourism Management and Expert Systems with Applications.

In The Last Decade

Theodoros Lappas

49 papers receiving 1.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Finding a team of experts in social networks

2009 444 citations Theodoros Lappas, Kun Liu et al. profile →

Peers

Theodoros Lappas

IS

AI

SPS

SNP

CSA

Aris Anagnostopoulos Italy

Wingyan Chung United States

Cheng–Te Li Taiwan

Pavel Serdyukov Russia

Sougata Mukherjea United States

Pasquale De Meo Italy

Alejandro Jaimes Spain

Liangjie Hong United States

Bee-Chung Chen United States

Huiji Gao United States

Aris Anagnostopoulos Italy

Theodoros Lappas

498 ×0.9

IS

514 ×1.1

AI

283 ×0.7

SPS

569 ×1.5

SNP

203 ×0.8

CSA

Citations per year, relative to Theodoros Lappas Theodoros Lappas (= 1×) peers Aris Anagnostopoulos

Countries citing papers authored by Theodoros Lappas

Since Specialization

Citations

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

Fields of papers citing papers by Theodoros Lappas

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Theodoros Lappas. 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 Theodoros Lappas. The network helps show where Theodoros Lappas may publish in the future.

Co-authorship network of co-authors of Theodoros Lappas

This figure shows the co-authorship network connecting the top 25 collaborators of Theodoros Lappas. A scholar is included among the top collaborators of Theodoros Lappas 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 Theodoros Lappas. Theodoros Lappas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

1.

Lappas, Theodoros, et al.. (2025). Principles for Responsible AI Consciousness Research. Journal of Artificial Intelligence Research. 82. 1673–1690. 3 indexed citations

2.

Li, Lun, et al.. (2023). Measuring employer attractiveness in diverse talent markets. Decision Support Systems. 177. 114079–114079. 3 indexed citations

3.

Haidopoulos, Dimitrios, Theodoros Lappas, Emmanouil Stamatakis, et al.. (2023). Thoracic epidural analgesia as part of an enhanced recovery program in gynecologic oncology: a prospective cohort study. International Journal of Gynecological Cancer. 33(11). 1794–1799. 2 indexed citations

4.

Kokkodis, Marios, Theodoros Lappas, & Sam Ransbotham. (2020). From Lurkers to Workers: Predicting Voluntary Contribution and Community Welfare. Information Systems Research. 31(2). 607–626. 36 indexed citations

5.

Lappas, Theodoros, et al.. (2020). The Importance of Interactions Between Content Characteristics and Creator Characteristics for Studying Virality in Social Media. Information Systems Research. 31(2). 576–588. 65 indexed citations

6.

Lappas, Theodoros, et al.. (2018). Unsupervised tip-mining from customer reviews. Decision Support Systems. 107. 116–124. 26 indexed citations

7.

Lappas, Theodoros, et al.. (2017). Strength in Numbers: Using Big Data to Simplify Sentiment Classification. Big Data. 5(3). 256–271. 2 indexed citations

8.

Pelechrinis, Konstantinos, Christos Zacharias, Marios Kokkodis, & Theodoros Lappas. (2017). Economic impact and policy implications from urban shared transportation: The case of Pittsburgh’s shared bike system. PLoS ONE. 12(8). e0184092–e0184092. 33 indexed citations

9.

Kokkodis, Marios & Theodoros Lappas. (2016). Realizing the Activation Potential of Online Communities. International Conference on Information Systems. 3 indexed citations

10.

Yang, Pei, Hongxia Yang, Haoda Fu, et al.. (2016). Jointly Modeling Label and Feature Heterogeneity in Medical Informatics. ACM Transactions on Knowledge Discovery from Data. 10(4). 1–25. 7 indexed citations

11.

Kokkodis, Marios & Theodoros Lappas. (2016). The Relationship Between Disclosing Purchase Information and Reputation Systems in Electronic Markets.. International Conference on Information Systems. 5 indexed citations

12.

Kotzias, Dimitrios, Theodoros Lappas, & Dimitrios Gunopulos. (2015). Home is where your friends are: Utilizing the social graph to locate twitter users in a city. Information Systems. 57. 77–87. 23 indexed citations

13.

Gionis, Aristides, Theodoros Lappas, Evimaria Terzi, & Konstantinos Pelechrinis. (2014). Customized Tour Recommendations in Urban Areas. D-Scholarship@Pitt (University of Pittsburgh). 24 indexed citations

14.

Golshan, Behzad, Theodoros Lappas, & Evimaria Terzi. (2014). Profit-maximizing cluster hires. 1196–1205. 23 indexed citations

15.

Golshan, Behzad, Theodoros Lappas, & Evimaria Terzi. (2014). Profit-Maximizing Cluster Hires. SSRN Electronic Journal. 1 indexed citations

16.

Gionis, Aristides, Theodoros Lappas, Konstantinos Pelechrinis, & Evimaria Terzi. (2014). Customized tour recommendations in urban areas. 313–322. 61 indexed citations

17.

Lappas, Theodoros, Marcos R. Vieira, Dimitrios Gunopulos, & Vassilis J. Tsotras. (2012). On the spatiotemporal burstiness of terms. Proceedings of the VLDB Endowment. 5(9). 836–847. 62 indexed citations

18.

Lappas, Theodoros, Konstantinos Pelechrinis, Michalis Faloutsos, & Srikanth V. Krishnamurthy. (2010). A simple conceptual generator for the Internet graph. 1. 1–6. 4 indexed citations

19.

Lappas, Theodoros & Dimitrios Gunopulos. (2010). Interactive recommendations in social endorsement networks. 127–134. 7 indexed citations

20.

Lappas, Theodoros, Kun Liu, & Evimaria Terzi. (2009). Finding a team of experts in social networks. 467–476. 444 indexed citations breakdown →

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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