Data Analysis - Tenders Global

Data Analysis

United Nations Children's Fund

tendersglobal.net

JOB DESCRIPTION

By the end of the century, almost half of the global population will be African. By 2035, Africa will have the largest and youngest workforce in the world. African youth have a unique opportunity to leverage this energy to drive prosperity and innovation in their communities and across the continent. However, despite this potential, youth voices and perspectives are often absent in decision-making processes and policies affecting Africa’s development.
To bridge this gap, the UNDP and UNV are implementing the Faces of Africa campaign. This initiative leverages the power and potential of visual storytelling to:
Document the aspirations, experiences, challenges, and solutions from African youth.
Communicate accurate, nuanced, and contextualized narratives about Africa.
Connect African youth to each other and to national and continental leadership.
Cultivate a community of young African leaders.

The analysis will cover the following:

Thematic Analysis: Identifying recurring themes in the stories.
Sentiment Analysis: Measuring the emotional tone of the stories.
Statistical Analysis: Quantifying thematic occurrences and patterns across demographics such as gender, region, and focus area.

Expected Deliverables

Thematic Report: A detailed breakdown of the main themes, sub-themes, and their frequencies.
Sentiment Report: A sentiment analysis report summarizing the emotional tone of the stories.
Statistical Report: A statistical analysis report with graphs and charts summarizing the key findings.
Visual Storytelling Assets: Infographics, charts, and word clouds to aid in visual storytelling.
Final Presentation: A consolidated presentation summarizing the findings and providing recommendations for future initiatives.

Qualitative Analysis Tools: NVivo, MAXQDA, or Atlas.ti for thematic coding and analysis.
Sentiment Analysis Tools: MonkeyLearn, Lexalytics, or manual coding for sentiment mapping.
Statistical Tools: Excel, R, or Python (pandas, matplotlib) for frequency counts, cross-tabulation, and visualization.
Visualization Tools: Power BI, Tableau, or Canva for creating graphs, charts, and visual summaries.


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