Data mining in social media for consumer satisfaction analysis

Social media sites such as Facebook, LinkedIn, and others have become vital data sources for organizations looking to get insights about customer satisfaction in the always changing social media landscape. This article explores the intricacies of data mining methods used by these platforms to interpret user opinions and satisfaction ratings

The process of extracting knowledge, patterns, and trends from enormous databases is called data mining. This procedure helps to uncover important details regarding user behavior, preferences, and satisfaction in the context of social media.

Commonly employed data mining techniques:

1. Text mining: Determining user sentiment by analysing textual data, such as posts, reviews, and comments.
2. Social Network Analysis: This technique looks at user relationships to pinpoint opinion leaders and influencers.
3. Machine learning algorithms: These utilise past data to forecast and categorise consumer preferences.(Gemes, 2021)