In the age of information explosion, social networking is twisted from the traditional media to the modern social media, followed by an emerging topic——social media analytics.
What is social media analytics?
According , normally driven by a specific target, social media analytics is basically informatics tools to extract, analyze and summarize then visualize the information from the collected data of social media. We can summarize the specific steps as follows:
- Put up with a problem
- Identifying the available data of social media
- Data collection: use web crawler or API tools.
- Analyze the data: some machine learning algorithms would be implied
- Present the results: summarization and visualization.
- Draw the conclusion
We can use an example to simply explain this. Someday a video become popular in a sudden——Chinese singer Cai Xukun is playing basketball in a strange way. After being reposted by 10 thousand times, the number of Cai Xukun’s followers is exceeding 20 million on Weibo. And we want to find out if someone is manipulating behind the sudden increment.
Why social media analytics is important？
From business perspective
For companies, sentiment analysis in social media would help them improve their products and adjust marketing strategies. Nowadays, people usually share their product or food experience in Instagram, Openrice or Xiaohongshu, etc. The companies could do sentiment analysis on their posts and see what people think of the products to improve their services or change marketing ways.
For customers, we can use social media analytics to detect the potential advertisements. As social media takes over our lives, some commercial advertisements could be hidden under the daily posts of some Internet celebrities. According to , there’re 60% of users know new products through Instagram. In Fig.4, up to 5k sponsored posts are sent in an hour on Instagram. To determine the true recommendations, you may need social media analytics.
From political perspective
Social media analytics could help to avoid the potential political influence. During the three debates of 2016 U.S. Election, Twitter manipulation could be involved through some highly automated activities. Highly automated accounts generated 4 pro-Trumps tweet to every pro-Clinton tweet in the first debate. Besides, through sentiment analytics, we could predict the election results by gauging people’s opinions on social media and plan for the next step at the first time.
Thank you for reading this blog, hope it can give you some different insights.
- Fig1: The picture of vintage social networking. Retrieved from https://wronghands1.com/2013/03/31/vintage-social-networking/
- D. Zeng, H. Chen, R. Lusch and S. Li, “Social Media Analytics and Intelligence,” in IEEE Intelligent Systems, vol. 25, no. 6, pp. 13-16, Nov.-Dec. 2010.
- Sentiment analysis engagement for a leading food service firm. Retrieved from https://apnews.com/58df0387e8dc46479849a6cb3078eb29
- The 43 Instagram Statistics You Need to Know in 2019. Retrieved from https://adespresso.com/blog/instagram-statistics/
- Sponsored Instagram Posts: How to Use Them (And How Not To Use Them). Retrieved from https://www.brandwatch.com/blog/react-sponsored-instagram-posts/
- Howard, Philip N., Bence Kollanyi, and Samuel Woolley. “Bots and Automation over Twitter during the US Election.” Computational Propaganda Project: Working Paper Series (2016).