Unique ID: 2015060

Division: Integration, Analysis, and Research
Issue Date: February 13th 2019
Last modified: February 22nd 2019
Collaborative

Use of data from social networks to obtain statistical and geographical information

Use of data from social networks to obtain statistical and geographical information

Exploration of different topics to review the feasibility of using information from Twitter to produce statistical and geographical information

Project Objective:

Exploration, Scientific / research

Project Outcomes:

Indicators on subjective well-being. Mobility maps of people among cities and across borders. Maps showing directions and flows of domestic tourism.

Project Sources
Project Sources
Type Of Institution: National statistical office
Big Data Source: Social media data
Region: Latin America & the Caribbean
Country Area: Mexico
Id Country Regional: country
Partnerships
Partnerships
Other Partners: Research or academic institute
Accessing Data
Accessing Data
Data Access Rights: Broader access rights
Data Coverage
Data Coverage
Data Coverage: Only a portion of all data
Coverage Geo Pop: Whole country / high % of market
Cost Implication: Free
Coverage Period: 2014/2015
Project Details
Project Details
Frequency Comments: Data with geospatial reference (longitude and latitude)
Data Quality
Data Quality
Quality Aspects Evaluated: Privacy and Security, Completeness, Usability, Time Factors, Accessibility, Relevance, Validity, Accuracy, including selectivity, Coherence, including linkability to other sources
Quality Framework Comments: No, because big data is a different paradigm.
Quality Assessment Comments: Completeness: we defined and obtained our own data of universe; Accuracy: check against tourism data is good; for subjective well-being data are confronted with those from surveys and we have a consistency of 80% ; Coherence: consistency across time.
Methodology
Methodology
Methods Used: Supervised learning, Decision Trees, Data visualization methods, Machine learning (Random forest, etc.)
Technologies
Technologies
Technologies: Relational database, NoSQL database, Data visualization tools, Hadoop Clusters, Cloud services
Other
Other
Income Level: Upper-middle-income
Iso: MX
Timeframe To Produce Indicator: NA
Frequency Comments: Data with geospatial reference (longitude and latitude)
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