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Scandal detector

Detect scandals for any entity, such as public firms or celebrities. The algorithm only requires sufficient search interest for a keyword and its associated scandals.

Project brief

Objective

Detect scandals for publicly known firms within the last 5 years.

Key results

  1. Show overall number of scandals
  2. Display scandals in timeline
  3. Provide links to Google for further investigation

Data

The project builds on Google Trends data. It covers search interest for a keyword over the last five years.

The data pipeline includes the following steps:

  1. a user inputs a keyword to which we add "scandal"
  2. the search interest is fetched from Google Trends with pytrends.
  3. Process the data with pandas
  4. train a time-series model with Facebook Prophet.
  5. Identify outliers from the predicted search interest. These are the scandals.
  6. Visualize timeline with plotly
  7. List links to Google in the period of the scandal

Extensions

  • check that detected scandals do not overlap within a period of `date_uppderbound_days
  • create config.yaml
  • load config with hydra

Color codings

Using color codings from http://towardssustainablefinance.com/.

color_discrete_sequence=["#4d886d", "#f3dab9", "#9bcab8", "#829fa5", "#cfaea5"] dark font color: #545454 bright background color: #D5E6E0