Hi. We are the Gold Diggers.

And this is our project, Analysis on Tweets Supposing the "Golden Era" during the FEM regime , where we dig through the reasons why the "Golden Era" is regarded as it is—hence, our name.

Data Science Team

  • Ma. Pauline Abcede, WFX
  • Carmelo Ellezandro Atienza, WFX
  • Calvin James Maximo, WFX

Here's an overview of our project.

The noise of misinformation and disinformation deafens the history and democracy of our country.

Motivation

With another Marcos seated in the position of President, the issue of historical distortion regarding the administration of former-President Ferdinand Marcos is more alarming than ever. As such, our team is motivated to contribute in any way we can in countering the dis/misinformation spreading rapidly through social media.

Problem

As we believe that education is the primary key in fighting dis/misinformation, it is important to identify which areas of learning we may need to work on more intensively to guide us in formulating a proper plan of action to counter the issue of historical distortion.

Solution

To find an answer to this question, our team plans to study dis/misinformative tweets implying how FEM's regime was a “Golden era” and identify which reason appears to be their most common claim. This should help us gain insights on how to approach our nation's problem on dis/misinformation regarding the FEM regime through education.

Problem Formulation

We lay out our foundation in tackling the tweets on the "Golden era" during the FEM regime.

Research Question

What were the most common reasons in dis/misinformative tweets supposing the “Golden era” during FEM regime?

Hypothesis

The dis/misinformative tweets were most likely to claim the strong government opposition against communism during the FEM regime, which led to the supposed “Golden era.”

Null Hypothesis

The dis/misinformative tweets were equally likely to claim various reasons that led to the supposed “Golden era” during the FEM regime.

Solution

Collect dis/misinformative tweets, identify each tweet's main reason for their claim, and tally and rank their reasons according to frequency.

Let's talk about our data science methodology.

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Here's what we found out.

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Results

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Results

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We'd like to hear from you.

You can add more information about the team members here.

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