Headline Analysis & Prediction Tool


Ukraine

“Молодий Буковинець" (translation: Young Bukovynian) newsletter is a dominant outlet among the regional editions. The news site covers local and national news, with an emphasis on the local news and events relevant to the citizens of the region. The readership is about 180K citizens of Bukovyna.

Strategy

The aim of the project was to implement an AI/ML feature to increase the reach by analyzing the headlines of the outlet and identifying the factors that contribute to the effectiveness of the headline.

The next step was to create a software solution that will assist authors with writing more effective headlines and predict whether a particular title will be successful according to the preferences of the target audience.

Execution

For this project, considering the potential high-load and machine learning features, we decided to use Google Cloud Platform, Docker, Python, Flask, Tensorflow, Keras, Jupyter, React.js.

Analysis: 

We have analyzed the dataset with the publications from the website for the following criteria:

  • View analysis correlation on two criteria: 2 hours after posting the piece and 24 hours after posting the piece
  • TF-IDF analysis to determine the importance of the specific words to a document in a corpus
  • LDA topic modeling to round up the relevant tag keywords.

The analysis was performed on a Python-based natural language pipeline Polyglot.

Results of Analysis:

As a result, we have constructed a correlation matrix that illustrates the dependence of these factors on the success rate of the headline. The graph includes the following correlations:

  • Publication time (2 and 24 hours after posting)
  • Entity count (including person, organization, and location count)
  • Title length, polarity, digits, and sentiment score

Outcome

The solution we got in the result became a foundation for the prototype of Headline Success Prediction Interface: the prototype works on a predictive model based on the AutoML predictions model and custom ML model.

Our client was happy with the way the product turned out and for us, it was a great opportunity to show our experience in the AI/ML technology. Win-win!

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