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Intro -- Preface -- Organization -- Software Product Categories in the Automotive Industry and How to Manage Them (Keynote) -- Contents -- Supporting Strategic Decision-Making for Selection of Software Assets -- Abstract -- 1 Introduction -- 2 Related Work -- 2.1 Decision-Making -- 2.2 Deciding on Origin -- 2.3 GRADE Taxonomy -- 2.4 Decision-Making in Software Business -- 3 Descriptive Models -- 3.1 Decision Model -- 3.2 Property Model -- 3.3 Context Model -- 4 Evidence-Based Knowledge Repository -- 5 Decision-Making Process -- 6 Summary and Further Work -- Acknowledgments -- References -- Software Analytics for Planning Product Evolution -- Abstract -- 1 Introduction -- 2 Background -- 3 Research Design -- 4 Analysis and Results -- 4.1 A Model for Analytics-Based Product Planning -- 4.2 Validation of the Model -- 5 Discussions -- 6 Conclusions -- Acknowledgments -- Appendix: Tables of Qualitative Analysis -- References -- Ecosystems Here, There, and Everywhere -- 1 Introduction -- 2 Background -- 3 Data and Research Method -- 4 Results -- 5 Discussion and Conclusions -- References -- PDISC - Towards a Method for Software Product DISCovery -- Abstract -- 1 Introduction -- 2 Foundations and Related Work -- 3 Research Method -- 3.1 Inclusion and Exclusion Criteria -- 3.2 Data Sources and Search Strategy -- 3.3 Data Extraction and Data Analysis -- 4 Results -- 5 Designing a Method for Software Product Discovery -- 6 The PDISC Method -- 7 Conclusion -- References -- Supporting the Evolution of Research in Software Ecosystems: Reviewing the Empirical Literature -- 1 Introduction -- 2 Related Work -- 3 Method -- 4 Analysis -- 5 Summary -- References -- A Survey of Modeling Approaches for Software Ecosystems -- 1 Introduction -- 2 Systematic Mapping Study -- 2.1 Research Context -- 2.2 Research Questions -- 2.3 Systematic Mapping -- 2.4 Search String.

Intro -- Preface to the SocInfo 2014 Proceedings -- Organization -- Contents -- City Labs -- City Labs - Introduction -- FlowSampler: Visual Analysis of Urban Flows in Geolocated Social Media Data -- 1 Introduction -- 2 Data -- 3 Related Work -- 4 Design -- 4.1 Data Transformation -- 4.2 Interface Components -- 5 Use Cases -- 5.1 Investigating Daily Routine in Trip Making Behaviour -- 5.2 Investigating Exceptional Trip Making Behaviour -- 6 Limitations, Uncertainty and Bias -- 7 Future Work -- References -- Policing Engagement via Social Media -- 1 Introduction -- 2 Related Work -- 3 Engagement Analysis -- 3.1 Expressing Engagement in Twitter -- 3.2 Machine Learning Analysis -- 3.3 Semantic Analysis -- 4 Discussions and Conclusions -- References -- Digital Social Media to Enhance the Public Realm in Historic Cities -- 1 Introduction -- 2 Relevant Works -- 3 Urbino: Why It Could Be Assumed as a Case Study -- 4 Data Mining Processes to Trace the Public Life of an Italian Historic City Center -- 5 A Strategy to Enhance the Public Life of Historic City Centers -- 6 Conclusion -- References -- Privacy Preserving Energy Management -- 1 Introduction -- 2 Analysis -- 2.1 Are Energy Logs Personal Data? -- 2.2 EMS User Groups and Their Access Rights -- 2.3 Design Strategies for Privacy by Design vs. Energy Control -- 3 Background -- 3.1 (Hardware) Virtualization -- 3.2 Attribute Based Encryption -- 4 Approach -- 4.1 Abstract EMS Architecture -- 4.2 Limitations of Privacy Enhancing Services -- 4.3 Logically Distributed EMS Based on CP-ABE and Virtualization -- 5 Evaluation and Discussion -- 6 Related Work -- 7 Conclusion and Future Work -- References -- DaTactic, Data with Tactics: Description and Evaluation of a New Format of Online Campaigning for NGOs -- 1 Introduction -- 2 DaTactic: Data with Tactics.

"Text contains both numerical examples and excerpts from contracts, in order to provide useful explanations followed by immediate practical cases"--

Intro -- Preface -- Organization -- Table of Contents -- Networks, Communities, and Crowds -- On Joint Modeling of Topical Communities and Personal Interest in Microblogs -- 1 Introduction -- 2 Related Work -- 2.1 Topic Analysis -- 2.2 Community Analysis -- 3 Topical Community and Personal Interest Model -- 3.1 Assumptions -- 3.2 Generative Process -- 3.3 Model Learning -- 3.4 Sparsity Regularization -- 4 Experimental Evaluation -- 4.1 Datasets -- 4.2 Evaluation Metrics -- 4.3 Performance Comparison -- 4.4 Background Topics and Topical Communities Analysis -- 5 Conclusion -- References -- Bridging Social Network Analysis and Judgment Aggregation -- 1 Introduction -- 2 Related Work -- 3 Judgment Aggregation -- 3.1 Basic Definitions -- 3.2 The Average Voter Rule -- 4 Social Network Analysis -- 5 TowardsaSocialNetwork -- 5.1 Matrix Translation -- 5.2 Relational Graphs -- 6 Theoretical Analysis -- 7 Empirical Analysis -- 7.1 Varying the Tuning Parameter -- 7.2 Experimental Setup -- 7.3 Results and Analysis -- 8 Simplifying the Social Network -- 9 Conclusions and Future Work -- References -- A Appendix: Proofs -- Friend Grouping Algorithms for Online Social Networks: Preference, Bias, and Implications -- 1 Introduction -- 2 Literature Review -- 3 Clustering Algorithms -- 4 Method -- 4.1 The Pre-interview -- 4.2 Facebook Grouping Application Use -- 4.3 The Post Interview -- 5 Evaluation -- 5.1 Evaluating Groups and Algorithms -- 5.2 Automation Bias -- 5.3 Exploring Group Dynamics without Ground Truth -- 6 Discussion -- 7 Conclusion -- References -- Appendix: Post-interview Questions -- The Influence of Indirect Ties on Social Network Dynamics -- 1 Introduction -- 2 Related Work -- 3 Datasets -- 4 Predicting Link Formation -- 4.1 Methodology -- 4.2 Experimental Results -- 5 Timing of Link Formation -- 5.1 Methodology -- 5.2 Experimental Results.

Christian Lucas investigates the effectiveness of sports sponsorships. Two empirical studies are conducted, based on a comprehensive literature review. Implications from both studies are derived that can guide sponsorship managers in their daily business. Successful sports marketing execution is more than purchasing a 30-second spot or signage in a stadium: It is to improve and enhance customer experience to be able to engage in a conversation with them. The first study analyses activation means by conducting a multi-level field study combining data about the sponsorship instruments of Bundes.