A study on the use of “Yams” for enterprise knowledge sharing

Text data understanding on social networking systems has become an important source of data for companies to understand their stakeholders better. The shift from pattern mining of structured database to non-structured text data has alerted companies to have a stronger presence in the new social media world. This research uses text miner module in the Statistical Analysis System (SAS) to analyze conversational data compiled from Yammer enterprise microblogging system. These inputs are used to study the topics discussed among employees. It is also used to examine the knowledge sharing activity among employees in the case company. This can be accomplished by analyzing the topics maps produced SAS software system. One is able to analyze the topic of discussion and the frequency of each topic on microblogging system platforms to observe the knowledge sharing and knowledge creation activity among employees. The case study company in this research project is a knowledge centric organization involves in knowledge sharing activity using a server-based Knowledge Management System (KMS). This research chooses employees that are involved in an active project. They will use Yammer instead of the current KMS system. The topic and text analysis diagrams are used to identify the patterns of discussion and the topics exchanged between employees. SAS (Statistical Analysis System) text mining tool is used to carry out the text mining analysis works where a number of visual representation graph were developed to study the communication patterns among employees. The results of this research had shown that text mining is able to surface employees' frequency of communication and topics of conversation through posting activities using Yammer in this research.