Abstract
Data Scientists write code, understand statistics and derive insights from data. Commonly used technologies include Relational Database Management Systems and Structured Query Language, ‘Big Data’ ecosystems such as Hadoop, R, Java, Python or similar code bases, and; Natural Language Processing software used to text-mine large un-/semi-/structured datasets. Data Scientists must also deploy complex software environments built on (or across) various physical, virtual and/or cloud computing infrastructures. This paper outlines the development of one such system designed to comprehensively analyse >8 million Twitter/Facebook social media posts.
| Original language | English |
|---|---|
| Publication status | Published - 18 Apr 2017 |
| Event | The GIS Research UK 25th Annual Conference - Manchester, United Kingdom Duration: 18 Apr 2017 → 21 Apr 2017 http://manchester.gisruk.org/proceedings.php |
Conference
| Conference | The GIS Research UK 25th Annual Conference |
|---|---|
| Abbreviated title | GISRUK2017 |
| Country/Territory | United Kingdom |
| City | Manchester |
| Period | 18/04/17 → 21/04/17 |
| Internet address |
Keywords
- data science
- big data
- social media
- text/data-mining
- analytics