Linda M. Seiter

543 total citations
13 papers, 292 citations indexed

About

Linda M. Seiter is a scholar working on Artificial Intelligence, Information Systems and Communication. According to data from OpenAlex, Linda M. Seiter has authored 13 papers receiving a total of 292 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 5 papers in Information Systems and 3 papers in Communication. Recurrent topics in Linda M. Seiter's work include Advanced Software Engineering Methodologies (6 papers), Software Engineering Research (4 papers) and Logic, programming, and type systems (3 papers). Linda M. Seiter is often cited by papers focused on Advanced Software Engineering Methodologies (6 papers), Software Engineering Research (4 papers) and Logic, programming, and type systems (3 papers). Linda M. Seiter collaborates with scholars based in United States and South Sudan. Linda M. Seiter's co-authors include Jens Palsberg, Karl Lieberherr, John M. Carroll and William D. Palmer and has published in prestigious journals such as IEEE Transactions on Software Engineering, Journal of Media Literacy Education and Social Science Computer Review.

In The Last Decade

Linda M. Seiter

13 papers receiving 272 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Linda M. Seiter United States 6 191 95 88 83 54 13 292
Samiha Marwan United States 11 280 1.5× 128 1.3× 147 1.7× 84 1.0× 30 0.6× 26 370
Barbara Demo Italy 4 236 1.2× 45 0.5× 99 1.1× 62 0.7× 21 0.4× 7 295
Tom Naps United States 10 273 1.4× 61 0.6× 136 1.5× 84 1.0× 51 0.9× 17 381
Dalton Guerrero Brazil 13 179 0.9× 96 1.0× 74 0.8× 162 2.0× 83 1.5× 39 369
Steve Roach United States 9 155 0.8× 67 0.7× 50 0.6× 122 1.5× 58 1.1× 36 325
Tobias Kohn United States 7 212 1.1× 102 1.1× 52 0.6× 73 0.9× 38 0.7× 21 317
Essi Isohanni Finland 6 268 1.4× 60 0.6× 99 1.1× 85 1.0× 50 0.9× 8 313
Dennis Brylow United States 11 154 0.8× 47 0.5× 44 0.5× 59 0.7× 56 1.0× 47 336
Diana Cukierman Canada 8 265 1.4× 82 0.9× 92 1.0× 85 1.0× 25 0.5× 31 401
Grant Braught United States 9 275 1.4× 43 0.5× 104 1.2× 167 2.0× 29 0.5× 35 383

Countries citing papers authored by Linda M. Seiter

Since Specialization
Citations

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

Fields of papers citing papers by Linda M. Seiter

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Linda M. Seiter. 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 Linda M. Seiter. The network helps show where Linda M. Seiter may publish in the future.

Co-authorship network of co-authors of Linda M. Seiter

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

All Works

13 of 13 papers shown
1.
Seiter, Linda M., et al.. (2022). Life of the Party: Social Networks, Public Attention, and the Importance of Shocks in the Presidential Nomination Process. Social Science Computer Review. 41(4). 1405–1419. 1 indexed citations
2.
Seiter, Linda M., et al.. (2020). Catch Me if You Can: Using a Threshold Model to Simulate Support for Presidential Candidates in the Invisible Primary. Journal of Artificial Societies and Social Simulation. 23(1). 2 indexed citations
3.
Seiter, Linda M., et al.. (2018). Teaching Social Justice: Intergenerational Service-Learning in Digital Media Course. Journal of Media Literacy Education. 10(1). 148–158. 4 indexed citations
4.
Seiter, Linda M.. (2015). Using SOLO to Classify the Programming Responses of Primary Grade Students. 540–545. 36 indexed citations
5.
Seiter, Linda M., et al.. (2013). Modeling the learning progressions of computational thinking of primary grade students. 59–66. 166 indexed citations
6.
Seiter, Linda M. & John M. Carroll. (2009). Computer Science and service learning: Empowering nonprofit organizations through open source content management systems. 4 indexed citations
7.
Seiter, Linda M.. (2007). Role annotations and adaptive aspect frameworks. 3–3. 3 indexed citations
8.
Seiter, Linda M., et al.. (2006). An aspect-oriented approach for modeling self-organizing emergent structures. 1997. 59–66. 6 indexed citations
9.
Seiter, Linda M., et al.. (2006). Emergence-Oriented Programming. 2. 1441–1448. 3 indexed citations
10.
Palmer, William D., et al.. (2005). Swarm reasoning. 12. 294–301. 2 indexed citations
11.
Seiter, Linda M., Jens Palsberg, & Karl Lieberherr. (1998). Evolution of object behavior using context relations. IEEE Transactions on Software Engineering. 24(1). 79–92. 39 indexed citations
12.
Seiter, Linda M., Jens Palsberg, & Karl Lieberherr. (1996). Evolution of object behavior using context relations. 46–57. 18 indexed citations
13.
Seiter, Linda M., Jens Palsberg, & Karl Lieberherr. (1996). Evolution of object behavior using context relations. ACM SIGSOFT Software Engineering Notes. 21(6). 46–57. 8 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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