Business Information Systems 22nd International Conference, BIS 2019, Seville, Spain, June 26–28, 2019, Proceedings, Part II

The two-volume set LNBIP 353 and 354 constitutes the proceedings of the 22nd International Conference on Business Information Systems, BIS 2019, held in Seville, Spain, in June 2019.
The theme of the BIS 2019 was "Data Science for Business Information Systems", inspiring researchers to share theoretical and practical knowledge of the different aspects related to Data Science in enterprises. The 67 papers presented in these proceedings were carefully reviewed and selected from 223 submissions. 

The contributions were organized in topical sections as follows:

Part I: Big Data and Data Science; Artificial Intelligence; ICT Project Management; and Smart Infrastructure.
Part II: Social Media and Web-based Systems; and Applications, Evaluations and Experiences.

Social Media and Web-based Systems.- Trends in CyberTurfing in the Era of Big Data.- Keyword-driven Depressive Tendency Model for Social Media Posts.- Exploring Interactions in Social Networks for Influence Discovery.- A literature review on application areas of social media analytics.- Personalized cloud service review ranking approach based on probabilistic ontology.- Influential Nodes Detection in Dynamic Social Networks.- A Fuzzy Modeling Approach for Group Decision Making in Social Networks.- System modeling by representing information systems as hypergraphs.- Development of a Social Media Maturity Model for Logistics Service Providers.- Potential benefits of New Online Marketing Approaches.- Applications, Evaluations and Experiences.- Using Blockchain Technology for Cross-Organizational Process Mining - Concept and Case Study.- Modeling the Cashflow Management of Bike Sharing Industry.- Predicting Material Requirements in the Automotive Industry using Data Mining.- Are Similar Cases Treated Similarly? A comparison between process workers.- Mining Labor Market Requirements Using Distributional Semantic Models and Deep Learning.- Enhancing Supply Chain Risk Management by Applying Machine Learning to Identify Risks.- Deep Neural Networks for driver identification using accelerometer signals from smartphones.- Dynamic Enterprise Architecture Capabilities: conceptualization and validation.- Re-engineering Higher Education Learning and Teaching Business Processes for Big Data Analytics.- Real-Time Age Detection Using a Convolutional Neural Network.- An Inventory-based Mobile Application for Warehouse Management to Digitize Very Small Enterprises.- Collaboration in Mixed Homecare - A Study of Care Actors' Acceptance towards Supportive Groupware.- Stress-Sensitive IT-Systems at Work: Insights from an Empirical Investigation.