Analyzing customer sentiments in microblogs - A topic-model-based approach for Twitter datasets. - Andreas Schieber; Stefan Sommer; Andreas Hilbert; Kai Heinrich (AMCIS, 2011)

Worüber reden die Kunden? - Ein modelbasierter Ansatz für die Analyse von Kundenmeinungen in Microblogs. - Andreas Schieber; Stefan Sommer; Kai Heinrich; Andreas Hilbert (GeNeMe, 2011)

Analyse von Konsumentenmeinungen in Microblogs: Topic-based Opinion Mining. - Andreas Schieber; Kai Heinrich; Andreas Hilbert (WSBI, 2011)

Methoden für Trendanalysen im Web zur Unter-stützungdes Customer Relationship Management. - Kai Heinrich; Andreas Hilbert; Martin Kersten (MKWI, 2012)

What is the Conversation About?: A Topic-Model-Based Approach for Analyzing Customer Sentiments in Twitter. - Stefan Sommer; Andreas Schieber; Kai Heinrich; Andreas Hilbert (Int. J. Intell. Inf. Technol., 2012)

Integration von Topic Models und Netzwerkanalyse bei der Bestimmung des Kundenwertes. - Kai Heinrich (GeNeMe, 2015)

The Missing Link - Predictive Models based on Textual and Dynamic Network Data. - Kai Heinrich (AMCIS, 2016)

Effective Visualizations of Energy Consumption in a Feedback System - A Conjoint Measurement Study. - Tobias Weiß 001; Madlen Diesing; Marco Krause; Kai Heinrich; Andreas Hilbert (BIS, 2016)

The missing link: a general prediction model based on textural and network data features. - Kai Heinrich (2016)

Are You up for the Challenge? Towards the Development of a Big Data Capability Assessment Model. - Patrick Zschech; Kai Heinrich; Marcus Pfitzner; Andreas Hilbert (ECIS, 2017)

Deep Intelligent Systems for Time Series Prediction: Champion or Lame Duck? - Evidence from Crude Oil Price Prediction. - Kai Heinrich; Vera Fleißner (AMCIS, 2018)

Analyzing Influences on Pivotal ITO Contract Features: A Quantitative Multi-Study Design with Evidence from Western Europe. - Michael Könning; Kai Heinrich; Patrick Zschech; Christian Leyh (AMCIS, 2018)

Towards an Open Book Architecture for Deep Learning Networks: Data Properties and Architectures - Evidence from Time Series Analytics. - Vera Fleißner; Kai Heinrich; Michael Seifert (LWDA, 2018)

Demystifying the Black Box: A Classification Scheme for Interpretation and Visualization of Deep Intelligent Systems. - Kai Heinrich; Patrick Zschech; Tarek Skouti; Jakob Griebenow; Sebastian Riechert (AMCIS, 2019)

Towards a Text-based Recommender System for Data Mining Method Selection. - Patrick Zschech; Kai Heinrich; Richard Horn; Daniel Höschele (AMCIS, 2019)

Everything counts: a Taxonomy of Deep Learning Approaches for Object Counting. - Kai Heinrich; Andreas Roth; Patrick Zschech (ECIS, 2019)

A Quantitative Analysis of Culture-induced differences in Pivotal IT Outsourcing Contract Features. - Michael Könning; Kai Heinrich; Christian Leyh; Markus Westner (ECIS, 2019)

Influencing Factors of Clinical Patient Recruitment Systems Design. - Jonathan Philipps; Kai Heinrich (HICSS, 2019)

Towards a Taxonomic Benchmarking Framework for Predictive Maintenance: The Case of NASA's Turbofan Degradation. - Patrick Zschech; Jonas Bernien; Kai Heinrich (ICIS, 2019)

Yield Prognosis for the Agrarian Management of Vineyards using Deep Learning for Object Counting. - Kai Heinrich; Andreas Roth; Lukas Breithaupt; Björn Möller; Johannes Maresch (Wirtschaftsinformatik, 2019)

Prognostic Model Development with Missing Labels - A Condition-Based Maintenance Approach Using Machine Learning. - Patrick Zschech; Kai Heinrich; Raphael Bink; Janis S. Neufeld (Bus. Inf. Syst. Eng., 2019)

Objekterkennung im Weinanbau - Eine Fallstudie zur Unterstützung von Winzertätigkeiten mithilfe von Deep Learning. - Kai Heinrich; Patrick Zschech; Björn Möller; Lukas Breithaupt; Johannes Maresch (HMD Prax. Wirtsch., 2019)

Fool me Once, shame on You, Fool me Twice, shame on me: a Taxonomy of Attack and de-Fense Patterns for AI Security. - Kai Heinrich; Johannes Graf; Ji Chen; Jakob Laurisch; Patrick Zschech (ECIS, 2020)

Vindictive Word-of-Mouth on Social Media Platforms - an Empirical Investigation of Drivers and their Measurement. - Marie-Christin Papen; Janine Göttling; Kai Heinrich; Lisa Kraus; Christian Leyh; Florian Siems (ECIS, 2020)

White, Grey, Black: Effects of XAI Augmentation on the Confidence in AI-based Decision Support Systems. - Jonas Wanner; Lukas-Valentin Herm; Kai Heinrich; Christian Janiesch; Patrick Zschech (ICIS, 2020)

How Much AI Do You Require? Decision Factors for Adopting AI Technology. - Jonas Wanner; Kai Heinrich; Christian Janiesch; Patrick Zschech (ICIS, 2020)

Die Rolle der mehrschichtigen Netzwerkanalyse im Bereich Social Media Analysis am Beispiel der Identifizierung von Persönlichkeitsmerkmalen. - Kai Heinrich; Adrian Fischer; Michael Seifert (Wirtschaftsinformatik (Zentrale Tracks), 2020)

Ein Vergleich aktueller Deep-Learning-Architekturen zur Prognose von Prozessverhalten. - Kai Heinrich; Patrick Zschech; Christian Janiesch; Markus Bonin (Wirtschaftsinformatik (Zentrale Tracks), 2020)

Intelligent User Assistance for Automated Data Mining Method Selection. - Patrick Zschech; Richard Horn; Daniel Höschele; Christian Janiesch; Kai Heinrich (Bus. Inf. Syst. Eng., 2020)

Adoption Barriers of AI: a Context-Specific Acceptance Model for Industrial Maintenance. - Jonas Wanner; Laurell Popp; Kevin Fuchs; Kai Heinrich; Lukas-Valentin Herm; Christian Janiesch (ECIS, 2021)

A Picture is Worth a Collaboration: Accumulating Design Knowledge for Computer-Vision-based Hybrid Intelligence Systems. - Patrick Zschech; Jannis Walk; Kai Heinrich; Michael Vössing; Niklas Kühl 001 (ECIS, 2021)

Stop Ordering Machine Learning Algorithms by Their Explainability! An Empirical Investigation of the Tradeoff Between Performance and Explainability. - Jonas Wanner; Lukas-Valentin Herm; Kai Heinrich; Christian Janiesch (I3E, 2021)

Process data properties matter: Introducing gated convolutional neural networks (GCNN) and key-value-predict attention networks (KVP) for next event prediction with deep learning. - Kai Heinrich; Patrick Zschech; Christian Janiesch; Markus Bonin (Decis. Support Syst., 2021)

Machine learning and deep learning. - Christian Janiesch; Patrick Zschech; Kai Heinrich (Electron. Mark., 2021)

Where was COVID-19 first discovered? Designing a question-answering system for pandemic situations. - Johannes Graf; Gino Lancho; Patrick Zschech; Kai Heinrich (ECIS, 2022)

Algorithms as a Manager: A Critical Literature Review of Algorithm Management. - Kai Heinrich; Minh Anh Vu; Anastasiia Vysochyna (ICIS, 2022)

The effect of transparency and trust on intelligent system acceptance: Evidence from a user-based study. - Jonas Wanner; Lukas-Valentin Herm; Kai Heinrich; Christian Janiesch (Electron. Mark., 2022)

Stop ordering machine learning algorithms by their explainability! A user-centered investigation of performance and explainability. - Lukas-Valentin Herm; Kai Heinrich; Jonas Wanner; Christian Janiesch (Int. J. Inf. Manag., 2023)

Are Our Predictions Healthy? A Comparative Meta-Analysis of Machine Learning Studies in Predictive Healthcare. - Kai Heinrich; Armin Keshavarzi (ECIS, 2024)