Google NLP Hack Series: Swahili Social Media Sentiment Analysis Challenge 🎙️

Google NLP Hack Series: Swahili Social Media Sentiment Analysis Challenge

Helping Eswatini

E50 000 SZL

Challenge completed ~2 years ago

Skills you will learn

Natural Language Processing

Classification

Sentiment Analysis

42 joined

29 active

Info Data Leaderboard

Start

Jul 27, 23

Sep 15, 23

Reveal

Sep 16, 23

About

Zindi Africa with EA ambassadors gathered Swahili contents (tweets) from Twitter that express sentiment about popular topics. For this purpose, we extracted 3 000 tweets using Tweepy and Twitter APIs.

The data was preprocessed by removing links, emoji symbols, and punctuations.

The collected tweets were manually annotated using an overall polarity: positive (1), negative (-1) and neutral (0).

Files

Description

Files

Shows the submission format for this competition, with the ‘ID’ column mirroring that of Test.csv and the ‘Label’ column containing your predictions. The order of the rows does not matter, but the names of the ‘ID’ must be correct.Values in the 'label' column should be -1, 0 or 1.

Resembles Train.csv but without the target-related columns. This is the dataset on which you will apply your model to.

Contains the label (target). This is the dataset that you will use to train your model.

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