Learn how to mine social media data to collect insights, monitor metrics, research competitors and improve the ROI of social campaigns.
Harvesting social media data differs from traditional communication methods (e.g., survey, experiment, and content analysis) in several ways. First, it is unobtrusive in nature. That means researchers are not actively intervening in the data collection process. It is amethod of collecting and ...
In classical Social Network Analysis (SNA), what counted as a “social tie” was fixed by available data collection methods. The emergence of large-scale unobtrusive data collection techniques has sparked renewed interest in the very idea of what counts as a “social tie.” Importantly, there h...
This article provides a critical review of methods in predicting MHS on social media, identifying 75 papers published between 2013 and 2018. We report on patterns of data annotation and collection, data bias management, pre-processing and feature selection, model selection, and validation. Our resul...
Social media posts incorporate real-time information that has, elsewhere, been exploited to predict social trends. This paper considers whether such information can be useful in relation to crime and fear of crime. A large number of tweets were collected
9.5.1.4“BIG DATA” for predictive analysis In the presence of larger amounts of heterogeneous and valuable data such as for sequencing data, social media, and cardiovascular images, datasets are becoming more complex and very difficult to analyze using traditional methods of statistics. AI approache...
Learner Outcomes: After taking this course, you will be able to: utilize various Application Programming Interface (API) services to collect data from different social media sources such as YouTube, Twitter, and Flickr; process the collected data - primarily structured - using methods involving corr...
In this context, the utilization of online social media platforms as valuable tools in healthcare settings has gained prominence, offering direct avenues for disseminating critical health information to the public in a timely and accessible manner. Propelled by the ubiquitous accessibility of the ...
Zeeschuimer is a browser extension that monitors internet traffic while you are browsing a social media site, and collects data about the items you see in a platform's web interface for later systematic analysis. Its target audience is researchers who wish to systematically study content on ...
Random Forest has been shown to perform comparatively as well as traditional spatial methods and is effective at solving spatial problems (Breiman, 2001; Fox et al., 2020; Manley and Egoh, 2022). For example, Manley and Egoh (2022) used social media data from Flickr along with social and...