Data and DNA: The Future of Social Media Mining

By Rosemarie Szostak, Ph.D., Nerac Analyst

Originally Published June 24, 2019

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Social Media Mining


Social media mining of consumers trends is not just for your marketing department anymore. It should be part of your overall corporate R&D/innovation toolkit.

The world is awash in data ranging from e-commerce, in-store data, and the supply chain. Today, big data has gotten even more significant due to the rise in social media. There are over 3 billion users of social media. While you read this sentence, hundreds of thousands of tweets, comments, pictures, and videos have posted. An astonishing 73% of marketers believe companies that fail to use social data analysis effectively won’t survive in the long run. Social data has the potential to inform every aspect of a business.

The Hidden Pot of Gold in Social Media Data Mining

Social media data mining is the growing tool on the block and is used to uncover patterns and trends from public social media platforms such as Facebook, Twitter, LinkedIn, Instagram, YouTube, blogs, Amazon, and others. There is now sophisticated software to not only mine the data, identify and filter spam but can help explain and visualize the results.

The use of real time social media data mining can be used in research and development by capturing and monitoring consumer sentiment about existing products, identifying things that consumers like about them or find annoying. Few people express such emotions in customer surveys, but they will tweet about it or post about their experiences on Facebook. R&D departments can use this information to be proactive in product revisions or modifications based on consumer interests and trends. What changes do present customers want in the next iteration of your product?

It can also help by identifying patterns to gauge interest in products you may have in your pipeline and add confidence that your decision to scrap a new product with features that are of little interest to the consumer before spending money to develop, manufacture, and launch it.

Social conversations can help you better understand competitor’s products, what is working for them, and what does not.

See What is Trending in Your Sector

Tracking tweets is a real-time way of understanding your manufacturing production cycle without having to wait 30 days until sales numbers come in. A simple example is that of following “purchase intent mentions” on Twitter. In the case of the fast food restaurant, Chipotle, the number of tweets concerning going to that particular chain began to sharply trend down, indicating a significant decrease in consumer patronage. When it was time to report quarterly earnings, sure enough, Chipotle announced that it did not meet expectations. However, this was already obvious from data mining Twitter in real time.

Social media analysis can help you identify potential problems quickly. Social media is dynamic. Oak Ridge National Laboratory (ORNL) demonstrated the value of real-time mining of social media by mining Twitter data for tweets about power outages using the twitter geotagging function. This is an example of personalizing by location using geospatial information and the content from Twitter. Only 1% of Twitter users geotag their tweets, but the sheer volume of tweets makes this low percentage representative of the Twitterverse. Using geotagging, ONRL produced a heat map of the US, showing where power outages were occurring in real time. Imagine the power of this technology to identify critical issues in your product or supply chain that are broken. Logistics managers can analyze weather events at locations and quickly adapt to a severe weather event that might impact receiving an order on time. How many times do grocery stores run out of milk, bread, beer, and wine when there is a significant weather event.

R&D design teams can use mined consumer sentiment data to better align new designs with what a consumer actually wants. As a case study, researchers from Nottingham Trent University collected consumer sentiment data on desk lamps. They sorted the data with likes and dislikes of a general desk lamp. The results showed that consumers liked desk lamps which were small, adjustable, bright but with a dimmer, that included a touch function, and more. Dislikes included unstable bases, poor reliability, dullness and excessive heat. The students used this information to design a new table lamp. Want to be on top of a potential problem with your product?

Data mining social media will be quicker than getting a knock on the door from a regulatory agency about a possible recall, and you will be more proactive in solving the problem.

Some companies are getting creative in their data mining. Several have turned to using DNA data. Last year Spotify partnered with to use DNA data to create unique playlists for individuals. A start-up company, GenoPalate, collects DNA info through saliva samples and analyzes physiological components like an individual’s ability to absorb specific vitamins or how fast they can metabolize nutrients. With this information, they provide a personalized diet. To make money, they also sell meal kits that use the information. Whether this level of use of DNA beyond identifying your haplogroup or genetic tendency towards certain diseases is wrapped in pseudoscience, not only time will tell but so will social media.

How Can Nerac Help?

The field of data mining software is rapidly evolving. Though Nerac does not undertake social data mining of big data, we can help you navigate the array of software that is out there and identify and advise you as to potential vendors who can help you stay on top of the game, be it a well-established company or a start-up.

Nerac is here to help. Contact us here to learn more.

About the Analyst

Rosemarie Szostak, Ph.D.

Rosemarie Szostak, Ph.D., advises companies on technology, patents, innovation and disruptive technology. She has 20 plus years of experience as a thought leader and analyst with broad technical knowledge in chemistry, materials and chemical engineering.

Academic Credentials

  • Post Doctoral Fellow, Chemical Engineering Department, Worcester Polytechnic Institute
  • Ph.D., Chemistry, University of California Los Angeles
  • M.S., Chemistry/Physics, Georgetown University

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