Jasmina Smailović
Impact in
- Human-Computer Interaction top 1%
- Digital Communication and Language
- Artificial Intelligence top 2%
- Sentiment Analysis and Opinion Mining
- Advanced Text Analysis Techniques
- Topic Modeling
- Text and Document Classification Technologies
Papers in
-
- Complex Network Analysis Techniques 4
- Opinion Dynamics and Social Influence 3
- Co-authors
- Igor MozetičBorut SlubanPetra Kralj NovakMiha GrćarMartin ŽnidaršičNada LavračVítor CerqueiraLuı́s Torgo
- Journals
- PLoS ONE (4 papers)Information Sciences (1 paper)Information Processing & Management (1 paper)Computación y Sistemas (1 paper)Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (1 paper)
- Partner nations
- SloveniaSwitzerlandPortugal
In The Last Decade
Jasmina Smailović
13 papers receiving 954 citations
Hit Papers
Peers
Comparison fields: 5 of 112
- Human-Computer Interaction 282
- Artificial Intelligence 605
- Communication 115
- Statistical and Nonlinear Physics 85
- Management Science and Operations Research 84
Countries citing papers authored by Jasmina Smailović
This map shows the geographic impact of Jasmina Smailović'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 Jasmina Smailović with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jasmina Smailović more than expected).
Fields of papers citing papers by Jasmina Smailović
This network shows the impact of papers produced by Jasmina Smailović. 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 Jasmina Smailović. The network helps show where Jasmina Smailović may publish in the future.
Co-authors
The 19 scholars most cited alongside Jasmina Smailović, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 21 | |
| 2 | 2018 | 1 | |
| 3 | 2017 | 29 | |
| 4 | 2016 | 128 | |
| 5 | Twitter sentiment for 15 European languages | 2016 | 7 |
| 6 | Empirical evidence of the limits of automatic assessment of fictional ideation. | 2016 | 3 |
| 7 | Sentiment of Emojis Hit paper breakdown → | 2015 | 488 |
| 8 | 2015 | 32 | |
| 9 | 2015 | 38 | |
| 10 | 2015 | 34 | |
| 11 | 2014 | 57 | |
| 12 | 2014 | 5 | |
| 13 | 2014 | 163 |
About Jasmina Smailović
Jasmina Smailović is a scholar working on Human-Computer Interaction, Statistical and Nonlinear Physics, Artificial Intelligence, Signal Processing and Management Science and Operations Research, having authored 13 papers that have together received 1.0k indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (6 papers), Advanced Text Analysis Techniques (4 papers), Complex Network Analysis Techniques (4 papers), Opinion Dynamics and Social Influence (3 papers), Spam and Phishing Detection (2 papers), Misinformation and Its Impacts (2 papers), Stock Market Forecasting Methods (2 papers) and Time Series Analysis and Forecasting (2 papers). The work is most often cited by research in Human-Computer Interaction (282 citations), Artificial Intelligence (605 citations), Communication (115 citations), Statistical and Nonlinear Physics (85 citations) and Management Science and Operations Research (84 citations). Jasmina Smailović has collaborated with scholars based in Slovenia, Switzerland and Portugal. Frequent co-authors include Igor Mozetič, Borut Sluban, Petra Kralj Novak, Miha Grćar, Martin Žnidaršič, Nada Lavrač, Vítor Cerqueira, Luı́s Torgo, Vid Podpečan and Stefano Battiston. Their work appears in journals such as PLoS ONE, Information Sciences, Information Processing & Management, Computación y Sistemas and Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT).
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.