— Jose Gonzalez

Data mining

Average sentiment score

Twitter simultaneously allows people to be heard and to hear, easily and in real time, bringing with it potentially fascinating and ground breaking insights for anybody trying to take the public’s pulse on a hot issue.  It is almost mandatory that so much benefit comes with its challenges, namely how to process the humongous amounts of data available every minute. Never one to shy away from some super number crunching, this post is the first one of a series on Twitter.

The chart above represents more than 200,000 mentions of the twitter account belonging to Mexico’s President Enrique Peña Nieto during the past 20 days. It is intended as a proxy of how popular the President of Mexico is on Twitter. Every tweet was analyzed and scored as either positive or negative. Then the total number of positive/negative tweets per hour was recorded and divided by the total number of tweets in that hour. The results show, that on average, Peña Nieto has had a positive sentiment score (0.54) but there are severe hourly negative spikes.

If you would like to know more about how the calculations were elaborated, continue reading

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Data Science in Mexico

This map shows the growth of Kaggle community in North America. That is the submissions by Data Scientists to Kaggle competitions. Among other striking facts is the small amount of submissions done in Latin America, specially in Mexico, compared to the population of other countries. Where is the Data Science in Mexico? What can we do to foster it?

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So true about data science. No explanations required. Source: Drew Conway

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mexico 1 copymexico 2 copy

Why Mexico is ? ¿Por qué México es? Check the following results in English and Spanish using Google’s auto-complete function. Google uses the most used search terms to complete your inquiry/question/remark. Moreover, it uses your IP address to adjust the results, that is where is your computer located. The following queries, albeit short, are illustrative between searches in both Spanish and English from somebody located in the Washington, DC area (me). Stay tune for another version with different locations.

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