A sentiment analysis-based machine learning approach for financial market prediction via news disclosures R Chiong, Z Fan, Z Hu, MTP Adam, B Lutz, D Neumann Proceedings of the genetic and evolutionary computation conference companion …, 2018 | 69 | 2018 |
The behavior of blockchain ventures on Twitter as a determinant for funding success S Albrecht, B Lutz, D Neumann Electronic Markets 30 (2), 241-257, 2020 | 53 | 2020 |
How Sentiment Impacts the Success of Blockchain Startups–An Analysis of Social Media Data and Initial Coin Offerings S Albrecht, B Lutz, D Neumann Proceedings of the Hawaii International Conference on System Sciences, 2019 | 34 | 2019 |
Negation scope detection for sentiment analysis: A reinforcement learning framework for replicating human interpretations N Pröllochs, S Feuerriegel, B Lutz, D Neumann Information Sciences 536, 205-221, 2020 | 22 | 2020 |
Predicting sentence-level polarity labels of financial news using abnormal stock returns B Lutz, N Pröllochs, D Neumann Expert Systems with Applications 148, 113223, 2020 | 21 | 2020 |
Sentence-level sentiment analysis of financial news using distributed text representations and multi-instance learning B Lutz, N Pröllochs, D Neumann arXiv preprint arXiv:1901.00400, 2018 | 21 | 2018 |
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 | 20 | 2023 |
Permutation flow shop scheduling with multiple lines and demand plans using reinforcement learning J Brammer, B Lutz, D Neumann European Journal of Operational Research 299 (1), 75-86, 2022 | 19 | 2022 |
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 | 16 | 2022 |
Understanding the role of two-sided argumentation in online consumer reviews: A language-based perspective B Lutz, N Pröllochs, D Neumann arXiv preprint arXiv:1810.10942, 2018 | 8 | 2018 |
Solving the mixed model sequencing problem with reinforcement learning and metaheuristics J Brammer, B Lutz, D Neumann Computers & Industrial Engineering 162, 107704, 2021 | 5 | 2021 |
Identifying linguistic cues of fake news associated with cognitive and affective processing: Evidence from NeuroIS B Lutz, MTP Adam, S Feuerriegel, N Pröllochs, D Neumann Information Systems and Neuroscience: NeuroIS Retreat 2020, 16-23, 2020 | 5 | 2020 |
Stochastic mixed model sequencing with multiple stations using reinforcement learning and probability quantiles J Brammer, B Lutz, D Neumann OR Spectrum 44 (1), 29-56, 2022 | 4 | 2022 |
Automated real estate valuation with machine learning models using property descriptions K Baur, M Rosenfelder, B Lutz Expert Systems with Applications 213, 119147, 2023 | 3 | 2023 |
The longer the better? the interplay between review length and line of argumentation in online consumer reviews B Lutz, N Pröllochs, D Neumann arXiv preprint arXiv:1909.05192, 2019 | 3 | 2019 |
Distributed streaming reconstruction of information diffusion: poster PM Fischer, I Taxidou, B Lutz, M Huber Proceedings of the 10th ACM International Conference on Distributed and …, 2016 | 3 | 2016 |
When machines trade on corporate disclosures: Using text analytics for investment strategies HC Schmitz, B Lutz, D Wolff, D Neumann Decision Support Systems 165, 113892, 2023 | 2 | 2023 |
Utilizing the omnipresent: Incorporating digital documents into predictive process monitoring using deep neural networks S Levich, B Lutz, D Neumann Decision Support Systems 175, 114043, 2023 | 1 | 2023 |
Information Overload in Processing Consumer Reviews: The Role of Argumentation Changes F Popp, B Lutz, D Neumann | 1 | 2022 |
Understanding the Role of Social Media in the Assessment of Retailer-Hosted Consumer Reviews B Lutz, N Pröllochs, D Neumann Australasian Conference on Information Systems, 2017 | 1 | 2017 |