scholarly journals Identification of Enterprise Social Network (ESN) Group Archetypes in ESN Analytics

2020 ◽  
Vol 24 ◽  
Author(s):  
Kai Riemer ◽  
Laurence Lock Lee ◽  
Cai Kjaer ◽  
Annika Haeffner
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Communities Of Practice ◽  
Activity Patterns ◽  
Project Teams ◽  
Clustering Techniques ◽  
Group Type ◽  
Enterprise Social Networks ◽  
Enterprise Social Network

With the proliferation of Enterprise Social Networks (ESN), the measurement of ESN activity becomes increasingly relevant. The emerging field of ESN analytics aims to develop metrics and models to measure and classify user activity to support organisational goals and outcomes. In this paper we focus on a neglected area of ESN analytics, the classification of activity in ESN groups. We engage in explorative research to identify a set of metrics that divides an ESN group sample into distinct types. We collaborate with Sydney-based service provider SWOOP Analytics who provided access to actual ESN meta data describing activity in 350 groups across three organisations. By employing clustering techniques, we derive a set of four group types: broadcast streams, information forums, communities of practice and project teams. We collect and reflect on feedback from ESN champions in fourteen organisations. For ESN analytics research we contribute a set of metrics and group types. For practice we envision a method that enables group managers to compare aspirations for their groups to embody a certain group type, with actual activity patterns.

A Framework to Analyze Enterprise Social Network Data

2016 ◽  
pp. 84-107 ◽  
Author(s):  
Janine Viol Hacker ◽  
Freimut Bodendorf ◽  
Pascal Lorenz
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Networking Sites ◽  
Network Data ◽  
Social Network Data ◽  
Network Analytics ◽  
Enterprise Social Networks ◽  
Data Engineering ◽  
Enterprise Social Network

Enterprise Social Networks have a similar set of functionalities as social networking sites but are run as closed applications within a company's intranet. Interacting and communicating on the Enterprise Social Networks, the users, i.e. a company's employees, leave digital traces. The resulting digital record stored in the platform's back end bears great potential for enterprise big data engineering, analytics, and management. This book chapter provides an overview of research in the area of Enterprise Social Networks and categorizes Enterprise Social Network data based on typical functionalities of these platforms. It introduces exemplary metrics as well as a process for the analysis of ESN data. The resulting framework for the analysis of Enterprise Social Network data can serve as a guideline for researchers in the area of Enterprise Social Network analytics and companies interested in analyzing the data stored in the application's back end.

A Semantic Model to Address Health Questions to Professionals in Healthcare Social Networks

2010 ◽  
pp. 84-103
Author(s):  
Francisco Echarte ◽  
José Javier Astrain ◽  
Alberto Córdoba ◽  
Jesús Villadangos
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Virtual Communities ◽  
Automatic Classification ◽  
Semantic Model ◽  
Ontological Model ◽  
The Creation ◽  
Medical Concepts

Internet social networks offer a wide variety of possibilities, including communication between users, sharing information, and the creation of virtual communities on many different subjects. One of these subjects is healthcare, where different social networks are now appearing and covering different objectives. In this chapter, a social network is described, where users can formulate healthcare questions that are automatically classified under concepts of a medical ontology and assigned to experts of each topic. These questions are then answered by healthcare expert physicians. This chapter includes a semantic classifying method that provides the automatic classification of questions by means of a medical ontology, based on the tags used to annotate them, and the previously classified questions. The chapter includes an ontological model that represents the questions, the assigned tags, the answers, the physicians, and the medical concepts.

Extending Social Network Diagrams for Large Scale Collaboration

2012 ◽  
pp. 1-13
Author(s):  
I.T. Hawryszkiewycz
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Web 2.0 ◽  
Large Scale ◽  
Policy Planning ◽  
Web 2.0 Technologies ◽  
Enterprise Social Networks ◽  
Cloud Technologies ◽  
Common Vision ◽  
Network Diagrams

The chapter provides a way for modeling large scale collaboration using an extension to social network diagrams called enterprise social networks (ESNs). The chapter uses the ESN diagrams to describe activities in policy planning and uses these to define the services to be provided by cloud technologies to support large scale collaboration. This chapter describes collaboration by an architecture made up of communities each with a role to ensure that collaboration is sustainable. The architecture is based on the idea of an ensemble of communities all working to a common vision supported by services provided by the collaboration cloud using Web 2.0 technologies.

Enterprise social networks as a supporting tool in the digital economy

2018 ◽  
Vol 4 (10) ◽  
pp. 273-279
Author(s):  
Jana Skoludova
Keyword(s):  
Social Networks ◽  
Information Technology ◽  
Digital Economy ◽  
Information Technology Management ◽  
The Czech Republic ◽  
Enterprise Social Networks ◽  
Internal Information ◽  
Enterprise Social Network ◽  
Business Sectors ◽  
Modern Technologies

Digital economy refers to an economy that is based on digital computing technologies. It is widely accepted that the growth of the digital economy has widespread impact on the economy as a whole. Companies have been trying to respond to the changes of the digital economy, and they have been integrating information technology management into their enterprises. The goal of this paper is to determine the benefits of Enterprise Social Networks in companies. The methodology of this paper is based on comparative qualitative research using a survey conducted in the Czech Republic across business sectors. The research focuses on costs related to the use of Enterprise Social Networks. The results indicate the possible use of modern technologies for more effective business management. This paper discusses the use of the latest trends and innovations concerning technologies to help managers effectively convey internal information within the digital economy. Keywords: Digital economy, information technology, enterprise social network.

Big Data Analysis for Terroristic Behavior Identification and Study Using Social Networks

2019 ◽  
pp. 197-235
Author(s):  
Yuriy V. Kostyuchenko ◽  
Victor Pushkar ◽  
Olga Malysheva ◽  
Maxim Yuschenko
Keyword(s):  
Social Networks ◽  
Big Data ◽  
Social Network ◽  
Data Analysis ◽  
Big Data Analysis ◽  
Stochastic Methods ◽  
Armed Groups ◽  
Conflict Zones ◽  
Analysis Of Dynamics

This chapter aimed to consider of approaches to big data (social network content) utilization for understanding social behavior in the conflict zones, and analysis of dynamics of illegal armed groups. The analysis directed to identify of structure of illegal armed groups, and detection of underage militants. The probabilistic and stochastic methods of analysis and classification of number, composition, and dynamics of illegal armed groups in active conflict areas are proposed. Data of armed conflict in Donbas (Eastern Ukraine) in the period 2014-2015 is used for analysis. The numerical distribution of age, gender composition, origin, social status, and nationality of militants among illegal armed groups has been calculated. Conclusions on the applicability of described method in criminological practice, as well as about the possibilities of interpretation of obtaining results in the context of study of terrorism are proposed.

The Contribution of Communities of Practice to Project Manamgement

2011 ◽  
pp. 104-107 ◽  
Author(s):  
Gillian Ragsdell
Keyword(s):  
Knowledge Management ◽  
Social Network ◽  
Project Management ◽  
Communities Of Practice ◽  
Cultural Change ◽  
Level Of Detail ◽  
Project Teams ◽  
Process Improvements ◽  
Opportunities For Learning ◽  
Potential Synergy

More and more organisations are using projects as a means of managing their business; increasingly, ‘new initiatives’ are the focus of organisational life. Such initiatives could include cultural change programmes, organisation redesigns, or process improvements. Tackling the sociological and psychological aspects of the project is a great enough challenge, but there is often a requirement to develop a technological dimension too. Accelerating technical advancements brings an extra level of complexity to the projects so that, in general, projects have become more complex—not only do they tend to have a wider variety of customers to satisfy, but they also tend to utilise more sophisticated technology and have more far-reaching implications than ever before. It is not too surprising that some projects ‘fail’; the increased complexity of projects brings an obvious rise in the associated risks. However, the increased complexity of projects also brings a rise in the opportunities for learning through the management of knowledge therein. These are opportunities that are not being fully exploited at present, as illustrated by the continuation of the ‘failure-to-learn’ and ‘learning-to-fail’ themes in the literature (e.g., Lyytinen & Robey, 1999; Cannon & Edmondson, 2004); a more active stance would consciously draw lessons from projects, from ‘successes’ and ‘failures’ alike. Parallel to the growing emphasis on projects in organisational life and their changing nature, there is growing recognition of the interplay between the fields of project management (PM) and knowledge management (KM). Reference has already been made to the opportunities for more effectively managing knowledge within a project setting. This article operates at a finer level of detail and draws attention to the potential synergy between project teams and a much popularised social network derived from the KM arena—that of communities of practice (CoP). In doing so, the disciplines of PM and KM are explicitly bridged and, it is put forward, the prospect of breaking the ‘learning-to fail’ and ‘failing-to learn’ loops is raised.

Social Network Analysis in Software Development Projects: A Systematic Literature Review

2020 ◽  
Vol 30 (03) ◽  
pp. 321-362
Author(s):  
Roland Robert Schreiber ◽  
Matthäus Paul Zylka
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Literature Review ◽  
Software Development ◽  
Systematic Literature Review ◽  
Project Teams ◽  
Development Projects ◽  
Project Organization

Software development in project teams has become more and more complex, with increasing demands for information and decision making. Software development in projects also hugely depends on effective interaction between people, and human factors have been identified as key to successful software projects. Especially in this context, managing and analyzing social networks is highly important. The instrument of social network analysis (SNA) provides fine-grained methods for analyzing social networks in project teams, going beyond the traditional tools and techniques of project management. This paper examines the importance of the application of SNA in software development projects. We conducted a systematic literature review (SLR) of research on software development projects and social network data published between 1980 and 2019. We identified and analyzed 86 relevant studies, finding that research on software development projects spans the topics of project organization, communication management, knowledge management, version and configuration management, requirement management, and risk management. Further, we show that most studies focus on project organization and that the most common method used to gather social data relies on automated extraction from various software development repositories in the SNA context. Our paper contributes to the software development literature by providing a broad overview of published studies on the use of social networks in helping software development projects. Finally, we identify research opportunities and make suggestions for addressing existing research gaps.

scholarly journals A Framework for Detecting Intentions of Criminal Acts in Social Media: A Case Study on Twitter

Information ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 154 ◽  
Author(s):  
Ricardo Resende de Mendonça ◽  
Daniel Felix de Brito ◽  
Ferrucio de Franco Rosa ◽  
Júlio Cesar dos Reis ◽  
Rodrigo Bonacin
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Online Social Networks ◽  
Communication Planning ◽  
Flexible Model ◽  
Selection Of

Criminals use online social networks for various activities by including communication, planning, and execution of criminal acts. They often employ ciphered posts using slang expressions, which are restricted to specific groups. Although literature shows advances in analysis of posts in natural language messages, such as hate discourses, threats, and more notably in the sentiment analysis; research enabling intention analysis of posts using slang expressions is still underexplored. We propose a framework and construct software prototypes for the selection of social network posts with criminal slang expressions and automatic classification of these posts according to illocutionary classes. The developed framework explores computational ontologies and machine learning (ML) techniques. Our defined Ontology of Criminal Expressions represents crime concepts in a formal and flexible model, and associates them with criminal slang expressions. This ontology is used for selecting suspicious posts and decipher them. In our solution, the criminal intention in written posts is automatically classified relying on learned models from existing posts. This work carries out a case study to evaluate the framework with 8,835,290 tweets. The obtained results show its viability by demonstrating the benefits in deciphering posts and the effectiveness of detecting user’s intention in written criminal posts based on ML.

Classification of Traffic Events Notified in Social Networks' Texts

2018 ◽  
pp. 6973-6984 ◽  
Author(s):  
Ana Maria Magdalena Saldana-Perez ◽  
Marco Antonio Moreno-Ibarra ◽  
Miguel Jesus Torres-Ruiz
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Social Network ◽  
Learning Algorithm ◽  
Relevant Information ◽  
User Generated Content ◽  
Machine Learning Algorithm ◽  
Information Processes ◽  
The Social

It is interesting to exploit the user generated content (UGC), and to use it with a view to infer new data; volunteered geographic information (VGI) is a concept derived from UGC, which main importance lies in its continuously updated data. The present approach tries to explode the use of VGI, by collecting data from a social network and a RSS service; the short texts collected from the social network are written in Spanish language; a text mining and a recovery information processes are applied over the data, in order to remove special characters on text, and to extract relevant information about the traffic events on the study area, then data are geocoded. The texts are classified by using a machine learning algorithm into five classes, each of them represents a specific traffic event or situation.

The Contribution of Communities of Practice to Project Management

2011 ◽  
pp. 2736-2740
Author(s):  
Gillian Ragsdell
Keyword(s):  
Knowledge Management ◽  
Social Network ◽  
Project Management ◽  
Communities Of Practice ◽  
Cultural Change ◽  
Level Of Detail ◽  
Project Teams ◽  
Process Improvements ◽  
Opportunities For Learning ◽  
Potential Synergy

More and more organisations are using projects as a means of managing their business; increasingly, ‘new initiatives’ are the focus of organisational life. Such initiatives could include cultural change programmes, organisation redesigns, or process improvements. Tackling the sociological and psychological aspects of the project is a great enough challenge, but there is often a requirement to develop a technological dimension too. Accelerating technical advancements brings an extra level of complexity to the projects so that, in general, projects have become more complex—not only do they tend to have a wider variety of customers to satisfy, but they also tend to utilise more sophisticated technology and have more far-reaching implications than ever before. It is not too surprising that some projects ‘fail’; the increased complexity of projects brings an obvious rise in the associated risks. However, the increased complexity of projects also brings a rise in the opportunities for learning through the management of knowledge therein. These are opportunities that are not being fully exploited at present, as illustrated by the continuation of the ‘failure-to-learn’ and ‘learning-to-fail’ themes in the literature (e.g., Lyytinen & Robey, 1999; Cannon & Edmondson, 2004); a more active stance would consciously draw lessons from projects, from ‘successes’ and ‘failures’ alike. Parallel to the growing emphasis on projects in organisational life and their changing nature, there is growing recognition of the interplay between the fields of project management (PM) and knowledge management (KM). Reference has already been made to the opportunities for more effectively managing knowledge within a project setting. This article operates at a finer level of detail and draws attention to the potential synergy between project teams and a much popularised social network derived from the KM arena—that of communities of practice (CoP). In doing so, the disciplines of PM and KM are explicitly bridged and, it is put forward, the prospect of breaking the ‘learning-to fail’ and ‘failing-to learn’ loops is raised.

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