Noteworthy Links: Social Media Edition

June 14th, 2016

Social media data is inexpensive, fast, and effortless to access. As a result, businesses are increasingly using data from social networking sites such as Twitter, Facebook, Youtube, and Google Search. For example, when compiling data for our Caltrain project, we found that sentiment on Twitter was highly correlated with train delays.

As more value is being realized from online communities, graph-based approaches are becoming increasingly important for mining social networks. Below are some links to interesting work being done with social media data. Are you working on a related project? Let us know in the comments.

Social Media and Mobile Shopping: Social media is becoming increasingly important in the world of mobile shopping, including calls to action, interactive ads, visual search, and improved ad targeting.

Introducing GraphFrames: At Spark Summit 2016, Databricks announced GraphFrames, a graph processing library for Apache Spark.

Social Network Analysis and Teachers: Social network theory may be a key tool in helping teachers. This article discusses case studies that suggest social networks can help teachers identify critical resources, among other benefits.

Social Network Analysis, Link Analysis, and Visualization: We’re linking to a list of links, but it’s worth it. KDD has put together a list of tools, including many open source software options.

Edge Prediction in a Social Graph: This Kaggle contest winner illustrates the challenges of modeling social network data.

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