Amanda Cierra Chavis

Major: BBA MIS
Graduation: May 2019

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MIS 2502
Social network analysis/analytics


Social media/network analytics is the technique of collecting data from social media websites and blogs, using the analysis to make business decisions.  This process is more thorough than “the usual monitoring or a basic analysis of retweets or ‘likes’” ( “What Are…”), as it turns the data into useful information to “develop an in-depth idea of the social consumer” (“What Are…”).  Before starting the process, it is important to “determine which business goals, [such as getting product and services feedback or improving public opinion] the data that is gathered and analyzed will benefit.” (Rouse).  Then, key performance indicators (KPIs) need to be identified in order to objectively evaluate the analysis.

Doing social network analytics allows businesses to see who their follower presence really is, what their feelings about the company are, and even if consumers will like an upcoming product or service.  It can even involve sentiment analytics, which uses “sophisticated natural-language-processing machine learning algorithms parsing the text in a person’s social media post about a company to understand the meaning behind that person’s statement” (Rouse) and even provide a score with the analysis.  Social media analytics is increasingly more important for companies to do because there is tons of information to be found in social media data.  It also can help save money in the long run.  Rouse comments in her article that “In decades past, enterprises paid market research companies to poll consumers and conduct focus groups to get the kind of information that consumers now willingly post to public social media platforms”.

In MIS 2502, we learn about unstructured data being that initial, raw data, before it is transformed into knowledge.  This unstructured data is what is gathered by the analytics tool; it is the data found in blog posts, Facebook posts, tweets, etc..  We also learned how to use the open source platform, R, and this platform can actual serve as one of many social media analytics tools (Rouse).  Additionally, when learning about relational data modeling, we learned about the cardinalities one-to-one and one-to-many, which define the rules of association between entities.  One advantage for companies to do social media analytics, according to Techopedia’s article, is that it enables them to “execute focused engagements like one-to-one and one-to-many”.  With all the information learned in MIS 2502, students are equipped with enough understanding in the various topics to give a successful try at social media analytics.


Sources:

Rouse, Margaret, and Ed Burns. “What Is Social Media Analytics? – Definition from WhatIs.com.” SearchBusinessAnalytics, June 2017,
searchbusinessanalytics.techtarget.com/definition/social-media-analytics.

“What Are Social Media Analytics (SMA)? – Definition from Techopedia.” Techopedia.com, www.techopedia.com/definition/13853/social-media-analytics-sma.


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