Social Network Analysis Extra Credit Assignment
Businesses should draw attention to what users are doing on social platforms and the type of demographics they are attracting. This is where social network analysis comes to play in guiding businesses to acquire, retain, and grow their customer base. It is an advanced analytics that analyzes connections, relationships, and behaviors of individuals and groups. The purpose is to track behavioral information through personal transactions and interactions for future potential revenue along with risks.
In order to analyze social network analysis, the data has to be collected from consumers’ network activity, which is then transformed into data visualization. The data can be collected from graphs and models that are also used as a customer relationship management system. This allows businesses to figure out buying patterns within their customer base. Also, it is a way for businesses to find ways to increase their customer population, marketing, and potential ideas. In MIS 2502, data visualization taught us how to detect data patterns, hidden structures, and condensing all the information. Data visualization allows a flow of communication of how well a business is doing.
In addition, social network analysis is related to MIS 2502’s topic of association rule mining. In the course, I was able to participate in assignments that taught us how calculate and analyze association between items. The overall objective is to predict the likelihood what items a customer will likely purchase together. In order to predict the occurrence of associations between items, we had to compute the support, confidence, and lift. The outcome of the support shows how often the market basket is appearing. If the confidence and lift is equal to or greater than one, it shows a stronger association in a market basket. Association rule mining and social network analysis are very similar in predicting the potential product demand that customers are likely to purchase. Both systems are great ways in expanding customer population, relationship, and satisfaction.
Citations:
“Communications Data Model Adapters and Analytics User’s Guide.” 7 Social Network Analytics, Oracle, 30 Sept. 2015, docs.oracle.com/cd/E64694_01/CDMAA/sna.htm#CDMAA1752.
Kobielus, James. “Social Media Analytics vs. Social Network Analysis.” InformationWeek, 27 July 2010, www.informationweek.com/software/information-management/social-media-analytics-vs-social-network-analysis/d/d-id/1091118.
“Social Network Analysis.” Wikipedia, Wikimedia Foundation, 10 Apr. 2018, en.wikipedia.org/wiki/Social_network_analysis.