Studying Microscopic Peer-to-Peer Communication Patterns

Gloor, Peter A.; Oster, Daniel; Putzke, Johannes; Fischbach, Kai; Schoder, Detlef; Ara, Koji; Kim, Taemie; Laubacher, Robert; Mohan, Akshay; Olguı́n, D.; Pentland, Alex; Waber, Benjamin N.

doi:10.2139/ssrn.1097111

Cited by 18 publications

(6 citation statements)

References 39 publications

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“…This article also points to potential for research and real world deployment above and beyond these questions: the approach can also be used to identify weaknesses in enterprise networks and as a decision making tool in the process of group reorganization (see Gloor et al 2007;Putzke et al 2008). Organizational charts often fail to ref lect the actual group structures within the enterprise, as occurring due to unplanned, informal communications.…”

Section: Open Research Questions and Potentialsmentioning

confidence: 99%

Analysis of Informal Communication Networks – A Case Study

Fischbach

Gloor

Schoder

2008

Bus. Inf. Syst. Eng.

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It is becoming more and more important for knowledge workers to increase their productivity. However, there is a general lack of (semi-)automated, IT-supported data collection and evaluation approaches that allow insights into the processes and structures of an enterprise's internal networks and the activities of its knowledge workers. The article presents a prototype of an IT-supported instrument ("Social Badges") that supports automatic collection of informal, personal interaction between (knowledge) workers within an enterprise. The authors' aim is to introduce a novel approach which improves data quality over legacy methods. The approach uses Social Network Analysis (SNA) to make it easier for executives to analyze and manage informal communications networks. Its practical applicability is demonstrated by a case study. IntroductionIf the formal organization is the skeleton of a company, the informal is the central nervous system driving the collective thought processes, actions, and reactions of its business units.( Krackhardt and Hanson 1993, p. 104) Both the volume and importance of knowledge workers are growing as industrialized countries go through structural changes towards service-oriented societies (Albach 1999;Drucker 1999;Davenport 2005). According to Apte and Nath (2007), knowledge workers already account for 70 % of the labor force in the USA and for more than 60 % of its added value. Despite the importance of knowledgeintensive work, little is known about how to improve it compared to manual work processes. This is because the work performed by knowledge workers is complex and hard to measure (Aral et al. 2006; Mangelsdorf 2008; Ramírez and Nembhard 2004). It can be assumed that the way information is exchanged and distributed will have an influence on the relative productivity of groups and actors (Aral et al. 2006;Cross et al. 2003). The modern enterprise's productivity, efficiency and the ability to innovate thus all require an efficient structure and culture with respect to the exchange of knowledge between employees ( Knowledge is mainly exchange via informal, social communication networks whose structures often differ greatly from the enterprise's organizational structure and workflows (Krackhardt and Hanson 1993). At the same time, these structures have a decisive influence on the ability of employees, workgroups and the whole enterprise to deliver superior performance as they determine how quickly information can be propagated across a network, or whether stake holding employees will be able to contact each other (Cross and Parker 2004). In this context Cross et al. (2003, p. 8) emphasize that "one of the most consistent findings in the social science literature is that whom you know often has a great deal to do with what you come to know".Within this context the management of informal communication networks between enterprise staff becomes strategically significant (Davenport and Prusak 1998;Cross et al. 2003;Berglind and Scales 1987). Knowledge management focuses on those parts o...

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Section: Open Research Questions and Potentialsmentioning

confidence: 99%

Analysis of Informal Communication Networks – A Case Study

Fischbach

Gloor

Schoder

2008

Bus. Inf. Syst. Eng.

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“…Weblinks and blogs can be accessed via Google's blogsearch and Microsoft's live search API. Data gathered with Social Badges can also be loaded into Condor [29]. Not natively supported data sources can be loaded into Condor via flat files or by parsing the data directly into a MySQL database.…”

Section: Group-average Agglomerative Clusteringmentioning

confidence: 99%

Adding Taxonomies Obtained by Content Clustering to Semantic Social Network Analysis

Fuehres¹,

Fischbach

Gloor³

et al. 2010

On Collective Intelligence

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Abstract. This paper introduces a novel method to analyze the content of communication in social networks. Content clustering methods are used to extract a taxonomy of concepts from each analyzed communication archive. Those taxonomies are hierarchical categorizations of the concepts discussed in the analyzed communication archives. Concepts are based on terms extracted from the communication's content. The resulting taxonomy provides insights into the communication not possible through conventional social network analysis.

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“…Wu used F2F networks and proximity data to explain information workers' productivity and found a cohesive network topology is associated with higher productivity [13]. Gloor [14] also used F2F network data in a bank, comparing them with email network data, and found that temporal oscillation in a particular F2F network parameter, i.e., betweenness centrality, is a good indicator representing the creativity of a group.…”

Section: A Socially Aware Systemsmentioning

confidence: 99%

Predicting flow state in daily work through continuous sensing of motion rhythm

Ara

Sato

Tsuji

et al. 2009

2009 Sixth International Conference on Networked Sensing Systems (INSS)

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We have constructed a new application of continuous sensing of human physiological data during daily a business setting. By capturing the subtle changes and differences in motion rhythm detected through an accelerator rather than trying to identify the context of human activities, we are envisioning the prediction of a person's psychological flow state, i.e., the engagement in one's task. A badge-shaped wearable sensor device called "Business Microscope" was developed and deployed in a real organization, an office supply firm, for one month to study how effectively flow states could be measured during daily work. We found that even though each subject behaved at different motion rhythms when they were in flow, the consistency of motion rhythm around 2 to 3 Hz was correlated with the richness of flow during work (r=0.47, p<0.01).

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Studying Microscopic Peer-to-Peer Communication Patterns

Cited by 18 publications

References 39 publications

Analysis of Informal Communication Networks – A Case Study

Analysis of Informal Communication Networks – A Case Study

Adding Taxonomies Obtained by Content Clustering to Semantic Social Network Analysis

Predicting flow state in daily work through continuous sensing of motion rhythm

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