Iqra Ameer
- Artificial Intelligence top 10%
- Information Systems
- Social Psychology
- Safety, Risk, Reliability and Quality
- Experimental and Cognitive Psychology
- Co-authors
- Grigori SidorovAlexander GelbukhRao Muhammad Adeel NawabBurcu CanHelena Gómez-AdornoNoman AshrafMuhammad IjazMuhammad Zahid
- Topics
- Sentiment Analysis and Opinion Mining (9 papers)Spam and Phishing Detection (5 papers)Text and Document Classification Technologies (4 papers)
- Partner nations
- MexicoUnited StatesPakistan
In The Last Decade
Iqra Ameer
17 papers receiving 189 citations
Peers
Comparison fields: 5 of 58
- Artificial Intelligence 140
- Information Systems 40
- Social Psychology 23
- Safety, Risk, Reliability and Quality 20
- Experimental and Cognitive Psychology 14
Countries citing papers authored by Iqra Ameer
This map shows the geographic impact of Iqra Ameer'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 Iqra Ameer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Iqra Ameer more than expected).
Fields of papers citing papers by Iqra Ameer
This network shows the impact of papers produced by Iqra Ameer. 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 Iqra Ameer. The network helps show where Iqra Ameer may publish in the future.
Co-authorship network of co-authors of Iqra Ameer
This figure shows the co-authorship network connecting the top 25 collaborators of Iqra Ameer. A scholar is included among the top collaborators of Iqra Ameer 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 Iqra Ameer. Iqra Ameer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 2 | |
| 8 | 3 | |
| 9 | 25 | |
| 10 | 9 | |
| 11 | 2 | |
| 12 | 31 | |
| 13 | 67 | |
| 14 | 20 | |
| 15 | Bots and Gender Profiling on Twitter. | 1 |
| 16 | 7 | |
| 17 | 11 | |
| 18 | Multi-lingual Author Profiling using Stylistic Features. | 1 |
| 19 | Identification of Author Personality Traits using Stylistic Features Notebook for PAN at CLEF 2015 | 5 |
About Iqra Ameer
Iqra Ameer is a scholar working on Artificial Intelligence, Information Systems and Social Psychology, having authored 19 papers that have together received 192 indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (9 papers), Spam and Phishing Detection (5 papers) and Text and Document Classification Technologies (4 papers). The work is most often cited by research in Artificial Intelligence (140 citations), Safety, Risk, Reliability and Quality (20 citations) and Information Systems (40 citations). Iqra Ameer has collaborated with scholars based in Mexico, United States and Pakistan. Frequent co-authors include Grigori Sidorov, Alexander Gelbukh, Rao Muhammad Adeel Nawab, Burcu Can, Helena Gómez-Adorno, Noman Ashraf, Muhammad Ijaz, Muhammad Zahid, Irfan Ullah and Zhengbing He. Their work appears in journals such as Scientific Reports, Expert Systems with Applications and IEEE Access.
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.