Data Quality Challenges in Twitter Content Analysis for Informing Policy Making in Health Care
2018
- 326Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage326
- Downloads193
- Abstract Views133
Artifact Description
Social media platforms and microblogs have become popular fora where the general public expresses opinions and concerns on a variety of matters. As a result, private and public organizations have been looking into ways for finding, understanding and communicating insights extracted from this massive amount of text-based interconnected data. There are, however, important difficulties associated with the noisiness and reliability of the content that hinder the analysis of the data. This paper reports the main challenges found in a real-world experience with social media used as a source of data to support policy making and assessment. We also propose a set of strategies for the precise retrieval of data, the profiling of social media users, and the involvement of policy makers in the analytical process.
Bibliographic Details
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