Ethiopian Political YouTube Channels Daily Statistics

This repository contains a Python script that collects daily statistics, such as view count, subscriber count, and video count, from a selected list of Ethiopian YouTube channels that have political proclivities or heavily discuss Ethiopian politics.

The script main.py has been running since January 01, 2023, see ./data/channels-data_01-2023.csv. The repo also includes R scripts for generating charts based on the collected data. You can use this repo to collect daily statistics of other YouTube channels, see the Usage section below.

Table of Contents

• Overview
• Requirements
• Installation
• Usage
• Visualizing Data
• Contributing

Overview

The purpose of this project is to gather daily insights and analyze the impact of Ethiopian political YouTube channels on their audience. By collecting and processing data such as view count, subscriber count, and video count, we can better understand the reach and influence of these channels in the Ethiopian political landscape, and identify which channels are more popular.

View a snapshot of stats

id	statistics.viewCount	statistics.subscriberCount	statistics.videoCount
Abc tv	200828	11600	131
Addis Compass Media / ACM / አዲስ ኮምፓስ ሚዲያ	14583797	72200	1058
AddisWalta - AW	60630014	459000	23112
Adebabay Media	14682322	107000	1035
Alpha Media አልፋ ሚዲያ	9614769	56000	1719
Andafta	317144179	988000	7769
Arat Kilo Media አራት ኪሎ ሚዲያ	712570	16500	90
DW Amharic	261164	9800	256
EBC	508033529	1490000	69427
EMS (Ethiopian Media Services)	94474168	370000	2592
ESAN TV	3087032	42600	106
ESATtv Ethiopia	213553058	699000	11359
EVN for Ethiopia	3051920	46500	242
Ethio Forum ኢትዮ ፎረም	328906250	830000	2103
Ethio News - ኢትዮ ኒውስ	39301147	194000	1836
Ethio News_ኢትዮ ኒውስ ቻናል 2	7504644	70800	251
Ethio Selam	2134367	67000	88
EthioTube	44496132	266000	1925
Fana Television	435002971	1480000	45473
Feta Daily News	249292345	827000	1872
GEBEYANU	14007827	139000	836
Horizon Free Media ሆራይዝን ነፃ ሚዲያ	3583645	49800	195
Mager Media - ማገር	2316530	34300	450
Mengizem Media ምንጊዜም ሚዲያ	8171838	69900	2501
OMN	143027902	683000	12456
Reyot	68142059	263000	2610
Roha	47947539	235000	2078
Terara Network	3727641	52800	285
Tigrai Media House	161231551	373000	6438
VOA Amharic	13280504	151000	7263
Wazema Radio	2692496	50300	1545
Zara Media Network - ዛራ	1291408	143000	0
ebstv worldwide	1360838470	2600000	26042
ዓባይ ዜና - Abbay News	33039618	440000	1979

Snapshot of stats as of 2024-08-01 23:05:10

Requirements

• Python 3.6 or higher
• google-api-python-client package
• R dependencies: data.table and ggplot2
• Quarto (for rendering chart.qmd)

Installation

1. Clone this repository:

   git clone https://github.com/eyayaw/ethio-youtube-channels.git

2. Change the directory to the cloned repository:

   cd ethio-youtube-channels

3. Install the required Python package:

   pip install -r requirements.txt

Usage

1. To use the script, you’ll need to obtain a Google API key. Follow the instructions in the Google API Console documentation to create a project and obtain an API key. Please read the YouTube Data API getting started.

2. Set the API key as an environment variable named YOUTUBE_DATA_API_V3_KEY : export YOUTUBE_DATA_API_V3_KEY=your_api_key

3. Update the  channels-list.csv  file with the list of YouTube channel IDs that you want to collect daily statistics about/from. Add one channel ID per row.

4. Run the script: python main.py

5. The script will generate a CSV file named  channels-data_MM-YYYY.csv  (where MM is the month and YYYY is the year, generated automatically as the script runs) in the  data  folder containing the daily statistics for each channel in the  channels-list.csv  file. Additionally, “static” information of the channels given in channels-list.csv will be written to data/channels-info.csv, and will be updated when new channels are added to the list.

Visualizing Data

1. Install the required R packages by running the following command in the R console: install.packages(c("ggplot2", "data.table"))

2. Open the  make-plots.R  script and modify the input file name to match the latest CSV file in the  data  folder.

3. Run the  make-plots.R  script to generate an interactive chart and save it as  chart.html.

4. Install Quarto and use it to render the  analysis.qmd  file.

Contributing

I highly welcome contributions to this project. If you want to add new features, fix bugs, or improve documentation, please submit a pull request or open an issue.

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Inspired by

1. Corey Schafer’s Python YouTube API tutorials, and
2. Patrik Loeber’s YouTube Data API tutorials