Sinequa, a leading software company, has developed an implicit social network. This unique network is based on the analysis of data interactions between employees within a company. Instead of the traditional approach of creating a network based on voluntary contributions and interactions, Sinequa’s implicit social network utilises Big Data and semantic analysis to map relationships and interactions.
By analysing the relationships between employees, their interactions, and the content they engage with, Sinequa can create a detailed map of the organisation’s social structure. This data-driven approach allows for a more accurate representation of the company’s social dynamics, as it is not reliant on self-reported data.
Sinequa’s implicit social network also provides valuable insights into the company’s knowledge flow. By mapping the interactions and relationships between employees, the network can identify key influencers and knowledge holders within the organisation. This can help companies better understand their internal dynamics and improve their information flow.
The network also has potential applications in the field of human resources. It can be used to identify potential talent, understand employee engagement, and even predict turnover. By utilising Big Data and semantic analysis, Sinequa’s implicit social network can provide valuable insights into the inner workings of a company.
Go to source article: http://www.duperrin.com/english/2014/01/07/implicit-social-network-according-sinequa/