Joseph D. Prusa

1.2k citations
28 papers · 772 indexed · 1 hit paper · h-index 13
Topics
Sentiment Analysis and Opinion Mining (17 papers)Spam and Phishing Detection (10 papers)Text and Document Classification Technologies (9 papers)

In The Last Decade

Joseph D. Prusa

27 papers receiving 730 citations

Hit Papers

Survey of review spam detection using machine learning te...2015202620182022201550100150200250

Peers

Joseph D. Prusa
Comparison fields: 5 of 108
  • Artificial Intelligence 559
  • Information Systems 362
  • Sociology and Political Science 158
  • Computer Networks and Communications 111
  • Signal Processing 81
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Citations per field
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Countries citing papers authored by Joseph D. Prusa

Since Specialization
Citations

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

Fields of papers citing papers by Joseph D. Prusa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joseph D. Prusa. 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 Joseph D. Prusa. The network helps show where Joseph D. Prusa may publish in the future.

Co-authorship network of co-authors of Joseph D. Prusa

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 14
2 0
3
Investigation of Maxout Activations on Convolutional Neural Networks for Big Data Text Sentiment Analysis.
2
4
Location-Based Twitter Sentiment Analysis for Predicting the U.S. 2016 Presidential Election.
6
5
Deep Neural Network Architecture for Character-Level Learning on Short Text.
3
6 15
7 14
8 1
9
Necessity of Feature Selection when Augmenting Tweet Sentiment Feature Spaces with Emoticons
1
10
Enhancing Ensemble Learners with Data Sampling on High-Dimensional Imbalanced Tweet Sentiment Data
10
11
Comparing Approaches for Combining Data Sampling and Feature Selection to Address Key Data Quality Issues in Tweet Sentiment Analysis.
3
12
Reducing Feature Set Explosion to Facilitate Real-World Review Spam Detection
19
13 6
14 8
15 28
16
Impact of Feature Selection Techniques for Tweet Sentiment Classification.
38
17
Survey of review spam detection using machine learning techniquesbreakdown →
295
18 6
19 104
20 36

About Joseph D. Prusa

Joseph D. Prusa is a scholar working on Artificial Intelligence, Information Systems and General Social Sciences, having authored 28 papers that have together received 772 indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (17 papers), Spam and Phishing Detection (10 papers) and Text and Document Classification Technologies (9 papers). The work is most often cited by research in Artificial Intelligence (559 citations), Information Systems (362 citations) and Signal Processing (81 citations). Joseph D. Prusa has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Taghi M. Khoshgoftaar, Mike Crawford, Aaron N. Richter, David J. Dittman, Amri Napolitano, Naeem Seliya, Paul Morris, Michael R. Lowe and Joffrey L. Leevy. Their work appears in journals such as Information Systems Frontiers, Journal Of Big Data and Social Network Analysis and Mining.

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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