Matthias Trier

The Use of Instant Messaging in Working Relationship Development: A Case Study

This article examines how Instant Messaging (IM) systems help employees of a Korean organization improve their relationships with their coworkers within and across organizational boundaries—within departments, between departments, and outside the organization. We briefly review literature about IM in developing working relationships and build our research questions. We then provide data analysis results based on a survey and structured interviews. Subsequently, in an exploratory case study of two individuals, we extend the analysis of departmental boundaries by including hierarchical levels, job profiles, and different communication purposes. Quantitative Social Network Analysis and visualization are used to analyze the communication pattern of the two individuals.

Research Note—Towards Dynamic Visualization for Understanding Evolution of Digital Communication Networks

The capabilities offered by digital communication are leading to the evolution of new network structures that are grounded in communication patterns. As these structures are significant for organizations, much research has been devoted to understanding network dynamics in ongoing processes of electronic communication. A valuable method for this objective is Social Network Analysis. However, its current focus on quantifying and interpreting aggregated static relationship structures suffers from some limitations for the domain of analyzing online communication with high volatility and massive exchange of timed messages. To overcome these limitations, this paper presents a method for event-based dynamic network visualization and analysis together with its exploratory social network intelligence software Commetrix. Based on longitudinal data of corporate email communication, the paper demonstrates how exploration of animated graphs combined with measuring temporal network changes identifies measurement artifacts of static network analysis, describes community formation processes and network lifecycles, bridges actor level with network level analysis by analyzing the structural impact of actor activities, and measures how network structures react to external events. The methods and findings improve our understanding of dynamic phenomena in online communication and motivate novel metrics that complement Social Network Analysis.

Mixed methods analysis of enterprise social networks

The increasing use of enterprise social networks (ESN) generates vast amounts of data, giving researchers and managerial decision makers unprecedented opportunities for analysis. However, more transparency about the available data dimensions and how these can be combined is needed to yield accurate insights into the multi-facetted phenomenon of ESN use. In order to address this issue, we first conducted a systematic literature review to identify available data dimensions and integrated them into a conceptual framework. We then adopted this framework as part of a mixed methods research approach to comprehensively analyze an empirical ESN case. With our results serving as a proof of concept we show the insights that can be derived from different data dimensions and how combining these can improve the validity of the analysis. The application of the framework also allows us to derive a detailed guideline for combining different data sources in ESN analysis to support researchers and decision makers.

The deep structure of organizational online networking - an actor-oriented case study

While research on organizational online networking recently increased significantly, most studies adopt quantitative research designs with a focus on the consequences of social network configurations. Very limited attention is paid to comprehensive theoretical conceptions of the complex phenomenon of organizational online networking. We address this gap by adopting a theoretical framework of the deep structure of organizational online networking with a focus on their emerging meaning for the employees. We apply and assess the framework in a qualitative case study of a large‐scale implementation of a corporate social network site (SNS) in a global organization. We reveal organizational online networking as a multi‐dimensional phenomenon with multiplex relationships that are unbalanced, primarily consist of weak ties and are subject to temporal change. Further, we identify discourse drivers and information retrievers as two mutually interdependent actor roles as an explanation for uneven levels of user contributions to the SNS. Based on our analysis, we elicit abstract order principles, such as topical discourses, and identify transactive memory theory as a potent explanation of the evolving interaction structures. We finally discuss how the deep structure framework can contribute to future research on organizational networks.

IT-Supported Visualization of Knowledge Community Structures

In the first part of this article, Communities of Practice are conceptually positioned as a very important and successful element of corporate Knowledge Management. By utilizing IT platforms they enable a direct connection of knowledge workers and the transfer and reuse of tacit expertise to geographically remote business problems. Although current Community Software provides its members with many sophisticated features, facilitators or moderators still lack functionalities to monitor, evaluate and communicate the development of their expert networks. After discussing the requirements of this special target group, this contribution concentrates on electronic discussions and proposes a software system for automatically analyzing the structure and value of Knowledge Communities by extracting available electronic data about their communication network. This includes the entities employee, topic, and document and their many relationships. Insightful structural visualizations based on theories of Network Analysis are introduced. They can be accessed and manipulated in a Management Cockpit to improve the transparency in communities.

Social Search: Exploring and Searching Social Architectures in Digital Networks

Content authors are increasingly using the Internet to network, providing each other with advice, collaboratively filtering important information, and creating virtual networks of trust. To adequately understand this social cyberspace, we must be able to search and explore the patterns and processes of group interaction. A novel software-based approach addresses this objective. The method is built on the concepts of social translucency and social network analysis, extending the latter by including keyword analysis, dynamic network visualization, and additional modeling properties. On the basis of these models, the authors suggest a visualization-based procedure for searching and exploring social corpora using combinable filtering algorithms. They offer two examples-an electronic discussion and a corporate email network-to demonstrate search and retrieval in networks. Their examples further yield novel insights into the actual dynamics of content dissemination and network evolvement among virtual network members.

Sympathy or Strategy: Social Capital Drivers for Collaborative Contributions to the is Community

Despite growing interest in delineating the social identity of Information Systems (IS) research and the network structures of its scholarly community, little is known about how the IS community network is shaped by individual conceptions and what motivates IS researchers to engage in research collaboration. Using an exploratory theoretical framework that is based on three dimensions of social capital theory, we examined 32 years of scientific co-authorship in an international IS researcher community. We formulated propositions to empirically examine the multi-level relationships between personal drivers and the resulting complex network organization of the IS community. Our propositions are refined with qualitative interviews and tested using a survey. This process revealed a collaborative research culture with several individual dispositions, including a strategic structural focus, a cognitive focus and a relational focus. These exist among actors displaying a range of differing behaviours such as active engagement and passive serendipity. Our study indicates individual differences at the conception stage of engaging in academic collaboration impact on the resulting network-level configuration. We identified that regional preference, maturity life cycles and lack of small-world properties highlight the important role of senior members as structural backbones and brokers within the IS community.

Analyzing the Dynamics of Community Formation Using Brokering Activities

During the past years, a growing attention on electronic collaboration and group formation among internet users but also among employees in knowledge related work context could be recognized. Indicators are the intensive discussion of the role of social software and web2.0 but also of corporate electronic communities of practice and knowledge management (e.g. Wasko and Faraj, 2000). This development invoked increased interest in observing, visualizing, analyzing, and even ‘measuring’ the structures of such networks.

Towards a Systematic Approach for Capturing Knowledge-Intensive Business Processes

Business process oriented Knowledge Management (KM) has two objectives: the design of KM Processes and the support of knowledge-intensive Business Processes. Existing approaches focus integrated Knowledge- and Process Management Systems, the support of processes with KM Systems, or the analysis of knowledge-intensive activities. All these applications require a systematic approach for the documentation of existing processes. Available procedural models propose steps for process oriented KM projects, but they rarely describe their implementation in concrete practical applications. That is why this contribution introduces a new process-oriented KM (POKM) project approach developed in corporate projects. A special focus is put on a detailed method for capturing knowledge intense processes which extends the existing broad perspective on KM projects. It allows for insights into questions like how to comprehensively capture expert processes, how to store the collected information in a structured way, and how to design supporting instruments and materials in order to generate a high quality data set, which subsequently is utilized to derive Knowledge Management measures.

Dissemination Patterns and Associated Network Effects of Sentiments in Social Networks

Communication in online social networks has been analyzed for some time regarding the expression of sentiments. So far, very little is known about the relationship between sentiments and network emergence, dissemination patterns and possible differences between positive and negative sentiments. The dissemination patterns analyzed in this study consist of network motifs based on triples of actors and the ties among them. These motifs are associated with common social network effects to derive meaningful insights about dissemination activities. The data basis includes several thousand social networks with textual messages classified according to embedded positive and negative sentiments. Based on this data, sub-networks are extracted and analyzed with a dynamic network motif analysis to determine dissemination patterns and associated network effects. Results indicate that the emergence of digital social networks exhibits a strong tendency towards reciprocity, followed by the dominance of hierarchy as an intermediate step leading to social clustering with hubs and transitivity effects for both positive and negative sentiments to the same extend. Sentiments embedded in exchanged textual messages do only play a secondary role in network emergence and do not express differences regarding the emergence of network patterns.