| Negativity drives online news consumption CE Robertson, N Pröllochs, K Schwarzenegger, P Pärnamets, ... Nature Human Behaviour 7 (5), 812-822, 2023 | 115 | 2023 |
| Business analytics for strategic management: Identifying and assessing corporate challenges via topic modeling N Pröllochs, S Feuerriegel Information & Management 57 (1), 103070, 2020 | 108 | 2020 |
| SentimentAnalysis: Dictionary-based sentiment analysis. R package version 1.3-2 S Feuerriegel, N Pröllochs Comprehensive R Archive Network (CRAN), 2018 | 76* | 2018 |
| Negation scope detection in sentiment analysis: Decision support for news-driven trading N Pröllochs, S Feuerriegel, D Neumann Decision Support Systems 88, 67-75, 2016 | 67 | 2016 |
| Russian propaganda on social media during the 2022 invasion of Ukraine D Geissler, D Bär, N Pröllochs, S Feuerriegel EPJ Data Science 12 (1), 35, 2023 | 62 | 2023 |
| Generating Domain-Specific Dictionaries Using Bayesian Learning N Pröllochs, S Feuerriegel, D Neumann Proceedings of the 23rd European Conference on Information Systems (ECIS), 2015 | 62 | 2015 |
| Enhancing sentiment analysis of financial news by detecting negation scopes N Pröllochs, S Feuerriegel, D Neumann Proceedings of the 48th Hawaii International Conference on System Sciences …, 2015 | 62 | 2015 |
| Community-based fact-checking on Twitter’s Birdwatch platform N Pröllochs International AAAI Conference on Web and Social Media (ICWSM) 16, 794-805, 2022 | 58 | 2022 |
| Investor reaction to financial disclosures across topics: An application of latent Dirichlet allocation S Feuerriegel, N Pröllochs Decision Sciences 52 (3), 608-628, 2021 | 50 | 2021 |
| Moral emotions shape the virality of COVID-19 misinformation on social media K Solovev, N Pröllochs Proceedings of the ACM Web Conference (WWW), 3706-3717, 2022 | 47 | 2022 |
| Emotions explain differences in the diffusion of true vs. false social media rumors N Pröllochs, D Bär, S Feuerriegel Scientific Reports 11 (1), 22721, 2021 | 47 | 2021 |
| Emotions in online rumor diffusion N Pröllochs, D Bär, S Feuerriegel EPJ Data Science 10 (1), 51, 2021 | 41 | 2021 |
| Detecting negation scopes for financial news sentiment using reinforcement learning N Pröllochs, S Feuerriegel, D Neumann Proceedings of the 49th Hawaii International Conference on System Sciences …, 2016 | 30* | 2016 |
| Affective information processing of fake news: Evidence from NeuroIS B Lutz, MTP Adam, S Feuerriegel, N Pröllochs, D Neumann European Journal of Information Systems, 1-20, 2023 | 27 | 2023 |
| Sentence-Level sentiment analysis of financial news using distributed text representations and multi-instance learning B Lutz, N Pröllochs, D Neumann Proceedings of the 52th Hawaii International Conference on System Sciences …, 2019 | 27 | 2019 |
| Are longer reviews always more helpful? Disentangling the interplay between review length and line of argumentation B Lutz, N Pröllochs, D Neumann Journal of Business Research 144, 888-901, 2022 | 26 | 2022 |
| Statistical inferences for polarity identification in natural language N Pröllochs, S Feuerriegel, D Neumann PloS one 13 (12), e0209323, 2018 | 26 | 2018 |
| Hate Speech in the Political Discourse on Social Media: Disparities Across Parties, Gender, and Ethnicity K Solovev, N Pröllochs Proceedings of the ACM Web Conference (WWW), 3656-3661, 2022 | 24 | 2022 |
| Negation Scope Detection for Sentiment Analysis: A Reinforcement Learning Framework for Replicating Human Interpretations N Pröllochs, S Feuerriegel, B Lutz, D Neumann Information Sciences, 2020 | 24 | 2020 |
| Learning interpretable negation rules via weak supervision at document level: A reinforcement learning approach N Pröllochs, S Feuerriegel, D Neumann Proceedings of the 2019 Conference of the North American Chapter of the …, 2019 | 24 | 2019 |
Stefan FeuerriegelProfessor, LMU Munich在 lmu.de 的电子邮件经过验证
