Projects / Local Chapter Challenge

Predicting Leadership Effectiveness on Twitter: The Role of Gender and Language Use

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This Omdena Local Chapter Challenge runs for 7 weeks and is a unique experience to try and grow your skills in a collaborative and safe environment with a diverse mix of people from all over the world.

You will work on solving a local problem, initiated by Coventry, England Chapter.

The problem

The problem that the above research aims to solve is the lack of understanding of how language use and audience engagement on Twitter may impact the perceived leadership effectiveness of male and female leaders. Additionally, it also aims to identify areas where gender bias may be present in the perceived leadership effectiveness of male and female leaders. By using machine learning techniques to predict perception quotient (PQ) scores based on the tweets of world leaders and examining the impact of gender on these scores, the research aims to provide a deeper understanding of how language use and audience engagement may affect the perceived effectiveness of leaders. This knowledge can help leaders, organizations, and society to recognize and address any gender bias present in leadership and improve the effectiveness of leaders.

The goals

The goals of the above research problem can be:

  • To predict world leaders’ perception quotient (PQ) scores based on their tweets using machine learning techniques.
  • To examine the impact of gender on the PQ scores and identify any gender bias present in the perceived leadership effectiveness of male and female leaders.
  • To understand the linguistic and engagement patterns of male and female leaders on Twitter.
  • To provide insight into how language use and audience engagement may impact the perceived effectiveness of leaders.
  • To identify areas where gender bias may be present in the perceived leadership effectiveness of male and female leaders.
  • To provide recommendations for leaders, organizations, and society to recognize and address any gender bias present in leadership and improve the effectiveness of leaders.
  • To contribute to the field of research on communication, gender and leadership by providing a comprehensive analysis of the influence of gender on the language use and audience engagement of world leaders on Twitter.

Why join? The uniqueness of Omdena Local Chapter Challenges

Omdena Local Chapter Challenges are not a competition or hackathon but a real-world project that will grow your experience to a new level.

A unique learning experience with the potential to make an impact through the outcome of the project. You will go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.

And the best part is that you will join the global and collaborative community of Omdena with tons of benefits to accelerate your career.

Read more on how Omdena´s Local Chapters work

First Omdena Local Chapter Challenge?

Beginner-friendly, but also welcomes experts

Education-focused

Open-source

Duration: 4 to 8 weeks



Your Benefits

Address a significant real-world problem with your skills

Build your project portfolio

Access paid projects (as an Omdena Top Talent)

Get hired at top organizations



Requirements

Good English

Suitable for AI/ Data Science beginners but also more senior collaborators

Learning mindset



This challenge is hosted with our friends at



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