Week 14 – Post Mortem

--Originally published at TC3045 – Sagnelli's blog


So last blog post I talked about my Database course project. We are using MongoDB as our backend along with Flask. We think is easier to implement python code with Flask than using exec functions on Node. Also, the learning curve of Node is way more difficult than Flask’s. Therefore, Flask is the winning framework to use. We won’t be using any agile methodology, since we started the project way too late. We are using XP methodologies to finish on time.

Stay tuned for this project’s advancements.

Election year: let’s be genuine, shall we?

--Originally published at TC3045 – Sagnelli's blog

2018 is an important year for Mexico, where the next six years are supposed to be defined by the Mexican people; however, corruption has always interfered with democracy, as the government has been accused of manipulating the votes.

Resultado de imagen para simpsons vote gif

This is the problem we are trying to solve with our project. Now, the important question is:

Who are we?

We are a group of students between 6th and 8th semester of Computer Science at Tec de Monterrey Campus Guadalajara:

  • Alfonso Contreras
  • Arturo González
  • Alejandro Vázquez
  • Michelle Sagnelli

What is our solution?

Basically, in one sentence, we are building a series of microservices that will let us determine who is the best acclaimed, and the most popular presidential candidate according to Twitter.

How are we supposed to do it?

We will apply data mining using Python Streaming Jobs, and Twitter’s API to temporarily store tweets in JSON’s. Afterwards, this data will be shown and saved for later use.

The challenge is to clean data by mining keywords, eliminating stopwords, and assigning tokens by tweet importance. Henceforth, this “clean” data will be used to analyze with machine learning the importance of this year’s candidates, and political parties. Finally, this information will be stored in JSON format for further analysis of political parties information, and candidates’ level of acceptance.


We are trying to implement location-based analysis of tweets, and being able to find which tweets belong to bots for achieving a more successful analysis.

This should be fun. I am very interested in this project, as it is challenging, and interesting. If you are interested too, do not hesitate in contacting me, and stay tuned with mine, and my colleagues’ , future blog posts.