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Twitter holds inside it a huge amount of information about all changes in the world that are coming every day. Since 2013, the number of Tweets each minute has increased 58% to more than 474,000 Tweets PER MINUTE in 2019! Now humans physically can't control all this flow of data. Our goal was to the monitoring of updates in the pharmaceutical industry to support competitive ability constantly.
1 Data Scientist, 1 Data Analyst
- Topic-modelling - Python - Natural language processing
Analyse 10 000+ of tweets
Prepare a visual understandable squeez of information in the last changes in the field
We provided an analysis of the EULAR conference with presentation of numerous pharmaceutical companies' solutions and activities. On the base of analysis, made the topic-modeling of social media activities. The data was processed with use of the natural language processing and Python
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