Social Network Analysis

Knowledge/Social Network Analysis Solutions

The development of Internet and mobile services forms connections structures between people, making us more dynamic and complex organisms.
Connection structures between people are becoming distribution channels of various data and contents, and have a number of effects on decision-making, including our purchasing activities.
Saltlux has analyzed the structure by extracting semantic social networks from social media, email, and vast corporate documents through knowledge/social network analysis solutions.
It has also established eDiscovery systems, intelligent security analyses, knowledge activity profiling, marketing strategies, experts’ recommendation, and search functions to solve problems by analyzing in-depth knowledge and mutual influence on networks.

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< Knowledge/Social Network Analysis Solutions Structure Diagram >

Overview

Network analyses, which are quantitative analysis methods to analyze relationship between objects (all objects including an agent) using graph theory, have various analysis methods according to the analysis target, among which social network analyses are often paramount. The current organizations are making efforts to find the new value of knowledge or use it for work or management through analysis of distribution and flow of knowledge. The organizations have various types of information (documents, email, the web, etc.) and can configure knowledge networks through analyses of these information resources. Generally, a knowledge network within an organization has the following benefits: Configuration of a knowledge network provides a basis for analyses of user types, knowledge flows, distribution channels of knowledge, and integration of knowledge dispersed within an organization.

Providing integrated knowledge within an organization
Generating integrated knowledge from partial knowledge by department and user.
Various knowledge flow information within an organization provides opportunities to communicate between knowledge groups.
Information about unspecific groups or certain subjects within networks can provide active opportunities to communicate between users or groups.
Minimizing work gaps through analysis of information between a knowledge holder and a knowledge provider within an organization
Analyses of generation, provision, and holding of knowledge by user/group can contribute to smooth coordination of work between users/groups.
Promoting mutual information sharing generally leads to an improvement in overall business capability
Easy discovery of and access to information related to work or an organization can improve business capability.

Main Features

  • Customer Problems

As communication channels become diversified and cooperative structures become complicated, it is becoming increasingly difficult to analyze the influence and marketing targets on social media with experts within an organization, as well as to understand cooperative structures within and beyond an organization.

  • Introduction Effects

Cost effective social marketing, experts’ recommendation to solve problems, effective knowledge management through character profiling, and establishment of security and eDiscovery systems through knowledge network analysis, and more.

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  • Main Functions

Network connection density, strength, analysis of various types of centrality, key figures by subject, proximate analyses of figures, analyses of related figures by subject, profiling of figures by related subject, analyses of connection paths, and others.

  • Built-in Products

STORM, RAINBOW, DISCOVERY and Interworking

  • Major Customers

Busan Metropolitan City Hall, Ministry of National Defense, KT, etc.

Detailed Functions

Knowledge networks are based on a social relationship network and a network of various subjects’ information occurring within an organization. Analyses of knowledge networks provides not only information of knowledge experts and knowledge brokers, but also the analysis results of user types, knowledge flow paths, and distribution channels of knowledge through analyses of social relationships and subjects. The data sources for analyses of knowledge within an organization and analysis methods are as follows:

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Knowledge networks configured within an organization enable various analyses and usages according to a certain point of view and provide a basis to easily access or utilize knowledge dispersed within an organization. Analyses of knowledge networks have the following characteristics.

Knowledge Flow Network Analysis
• Network to show from whom to whom useful knowledge for work flows
• Understanding of business knowledge flow by department and rank
Analyses of knowledge holders and providers
• Analyses of people who not only provide knowledge but also who obtain large amounts of knowledge from others
• Analyses of people hubs to distribute knowledge
Analyses of Potential CoP (Communities of Practice)
• Analyzing a group of people who make knowledge and expertise in a field more deeply through continuous interaction, sharing a passion for a certain subject, group of problems, and other concerns.
• CoP analyses are used to discover potential groups through knowledge flow network analyses
• An informal group formed as the result of natural knowledge flow, irrespective of department and organization
• Enables analyses and definition of a group of people consisting of active networks
Analyses of the Shortest Path
• Analyses of the shortest path to reach a person who holds knowledge related to the user

Knowledge Network Use

Let us explain how to configure a knowledge network from information that an organization has and to utilize it to form the characteristics of a knowledge network. Basically, an organization shares various types of work information within itself through email systems. How to apply networks configured through analyses of data sources, which can configure networks like email systems used within an organization to work, is as follows: Email-based networks are configured based on email sending and receiving and knowledge flow configures knowledge networks through analyses of entities existing on networks. How to use it is as follows:

Searching for experts

  • Finding the shortest path to reach experts through networks connected around oneself
  • Looking for documents held by experts or brokers connected with he user
  • Asking brokers or experts for information

Analyses of potential knowledge communities

  • Analyses and definition of a group of people consisting of active network
  • Defining of a network group after finding a network group consisting of each period and understanding knowledge flow

Knowledge Flow Network Analyses

  • Frequency of sending and receiving certain information
  • Frequency of appearance of search keywords by each user in each time period
  • Frequency of appearance of search keywords in each time period

Knowledge holders and providers

  • People who have or provide a large amount of a certain type of knowledge

Finding knowledge brokers

  • People hub who distributes a large amount of a certain type of knowledge

Networks within an organization can encounter problems like privacy infringement and supervision of members; however, finding various knowledge classes within anorganization has more benefits.

Features

Knowledge networks are based on a social relationship network and a network of various subjects’ information occurring within an organization. Analyses of knowledge networks provides not only information of knowledge experts and knowledge brokers, but also the analysis results of user types, knowledge flow paths, and distribution channels of knowledge through analyses of social relationships and subjects. The data sources for analyses of knowledge within an organization and analysis methods are as follows:

Real-time network analyses through a social network analysis algorithm

  • Analyses of Centrality
  • Cluster Analyses
  • Analyses of the Shortest Path

SSP (Service Strategy Planning)

  • Automated establishment of semantic data-based networks
  • Searching for subjects through content indexing
  • Automatic generation of networks for searched subjects
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Expansion of subject networks through analysis of subject relatedness

  • Extraction of related subjects
  • Integrated configuration of networks of related subjects
  • Statistics for figures about related subjects

HTML5-based Visualization

  • Provision of basic visualization
  • Easy expansion and changing of a phase
  • Provision of standard data interface
  • To interwork with other visualization controls