Social Media Data Mining
Fifteen years ago, social networks didn’t exist. Today, more than 1 billion people log in to Facebook more or less regularly to share articles, photos and connect with “friends.” Through this “living” information archive and others like it, social networks provide an unprecedented volume and variety of both personal and impersonal information that can be a valuable, if messy goldmine of intelligence.
The practice of social media data mining collects and processes of unstructured information (things such as posts, comments, tweets, images) shared on networks like Facebook and Twitter.
The information collected may be used in many different ways, such as for identifying current and future trends, creating social profiles, capturing consumer insights or for creating a rich knowledge base from users’ clicks users across the web. By analyzing the data in real time, social media data mining can also contribute to more sophisticated predictive modeling.
Leveraging AI and cognitive technology for social media data mining
Social media data mining powered by AI and cognitive technologies can provide even more powerful intelligence from the information gathered from social media. The key is its understanding of language, meaning and context. To capture the unique and personal ways that customers express themselves on social media requires understanding the nuanced locution, influence and consequence expressed in language.
The Cogito cognitive technology understands the unique aspects of the way users communicate on social media such as through slang, jargon, acronyms and abbreviations. In this way, the technology helps users hear and understand the voices on social media through a comprehension of content, context, intent and sentiment expressed in information.
Use of Social Media Data Mining
To get an idea of the reach of social media, consider that, in the 2016 US presidential election, more than one billion election related tweets were posted on Twitter from the first presidential debate until the day before the election. Here, it became the go-to place for conversations and reactions about breaking news and sharing opinions. According to this article from TechCrunch, social media was much more effective than traditional polls in predicting the eventual outcome of the election.
Therefore, it’s no surprise that social media data mining software is being applied in many areas. Companies, political parties, social and religious groups and others exploit the conversations and comments shared on social networks to gather information and intelligence to fuel research on markets, competitors, customers, competitors and more.
For a look at how a cognitive technology can be applied for social media data mining, explore our Expert IQ Reports where we analyze Tweets covering politics, sports, popular culture and other topics.