David Zimbra

2.1k citations
19 papers · 1.6k · 1 hit paper · h-index 13

Impact in

Papers in

David Zimbra

19 papers receiving 1.5k citations

David Zimbra's Hit Papers

Twitter brand sentiment analysis: A hybrid system using n-gram analysis and dynamic artificial neural network 2013 · 347 citations
3470+4+8Years since publication100200300

Peers

David Zimbra
Comparison fields: 5 of 101
  • Management Science and Operations Research 317
  • Artificial Intelligence 751
  • Information Systems 326
  • Communication 78
  • Ocean Engineering 146
Replace M. Ghiassi with:
M. Ghiassi United States
Qiang Wei China
Hamid Nemati United States
Stefan Dietze Germany
Jarosław Jankowski Poland
Jin‐Xing Hao China
Xijin Tang China
Mamata Jenamani India
Qing Zhu China
Nitin Indurkhya United States
David Zimbra relative to M. Ghiassi United States M. Ghiassi's profile →
Citations per field
00.5×1.5×2.3×
M. Ghiassi · 1×
Citations per year

Countries citing papers authored by David Zimbra

Since Specialization
Citations

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

Fields of papers citing papers by David Zimbra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside David Zimbra, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with David Zimbra Line = papers co-authored together David Zimbra links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1
Twitter brand sentiment analysis: A hybrid system using n-gram analysis and dynamic artificial neural network
Hit paper breakdown →
2013347
2 2008204
3 2004190
4 2018158
5 2010153
6 2010135
7 2005134
8 201659
9 201654
10 201439
11 201026
12
User-Generated Content on Social Media: Predicting Market Success with Online Word-of-Mouth
201021
13 201712
14 201411
15
ASSESSING PUBLIC OPINIONS THROUGH WEB 2.0: A CASE STUDY ON WAL-MART
20099
16 20158
17 20128
18 20113
19
Stakeholder and sentiment analysis in web forums
20121

About David Zimbra

David Zimbra is a scholar working on Artificial Intelligence, Sociology and Political Science, Statistical and Nonlinear Physics, Information Systems and Management Science and Operations Research, having authored 19 papers that have together received 1.6k indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (9 papers), Advanced Text Analysis Techniques (8 papers), Complex Network Analysis Techniques (6 papers), Digital Marketing and Social Media (4 papers), Spam and Phishing Detection (3 papers), Topic Modeling (3 papers), Digital Games and Media (3 papers) and Stock Market Forecasting Methods (2 papers). The work is most often cited by research in Management Science and Operations Research (317 citations), Artificial Intelligence (751 citations), Information Systems (326 citations), Communication (78 citations) and Ocean Engineering (146 citations). David Zimbra has collaborated with scholars based in United States and China. Frequent co-authors include M. Ghiassi, H. Saidane, Hsinchun Chen, Hsinchun Chen, Ahmed Abbasi, Jay F. Nunamaker, Daniel Zeng, Sean Lee, Chen and Zhang. Their work appears in journals such as Decision Support Systems, ACM Transactions on Management Information Systems, International Journal of Forecasting, Electric Power Systems Research and Expert Systems with Applications.

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.

Explore authors with similar magnitude of impact