Tracking changes in user-generated textual content on social media computing platforms

摘要

Social media posts related to a topic are analyzed over time by parsing the posts to identify terms and by statistically analyzing occurrences and co-occurrences of the terms in the posts to derive metrics. A relationship-based structure is updated over time based on the metrics. A relationship-based structure is updated over time based on the metrics. In an example, the relationship-based structure includes weighted nodes and edges. The nodes represent terms in the posts and the edges represent co-occurrences of the terms. The weights of the nodes depend on frequencies of the occurrences, while as the weights of the edges depend on frequencies of the co-occurrences. A trend in the social media posts is detected by identifying a change over time in the relationship-based data structure.