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Influencer Self-Disclosure Practices on Instagram: A Multi-Country Longitudinal Study

Description

This repository contains scripts and utilities for experiments related to the paper "Influencer Self-Disclosure Practices on Instagram: A Multi-Country Longitudinal Study". The main script is designed to collect and process data from Instagram using the CrowdTangle API.

Prerequisites

  1. Python: The project requires Python 3.9 or higher.

  2. CrowdTangle API Token: An API token for CrowdTangle is required to fetch data. This token should be set in a .env file in the root directory of the project, under the key API_TOKEN.

    Example:

    API_TOKEN="YOUR_API_TOKEN_HERE"

CSV File Format: dataset_accounts.csv

This file serves as the metadata input for your Instagram data collection and processing. Each row represents an individual Instagram account's metadata. The CSV consists of the following columns:

  1. username (required): The Instagram handle or username of the account.

  2. country (optional): A country code that represents the primary audience or location of the account.

  3. size(optional): The categorization of the account based on its following size (e.g. micro or mega)

  4. number_of_posts (optional): The total number of posts made by the account up to the last date of collection.

  5. followers_collection_time (optional): The follower count of the account at data collection time.

  6. first_post (required): The earliest date and time (in the format 'YYYY-MM-DD HH:MM:SS') from which posts should be collected for the respective account

  7. last_post (required): The latest date and time (in the format 'YYYY-MM-DD HH:MM:SS') until which posts should be collected for the respective account.

Example:

username,country,size,number_of_posts,followers_collection_time,first_post,last_post
ab_bowen,US,mega,3652,1626210,2013-06-24 14:01:12,2022-09-15 06:32:49
achrafhakimi,DE,mega,612,10162234,2014-01-19 19:49:42,2022-09-16 12:39:47

Setup & Installation

  1. Clone the repository:

    git clone https://github.com/thalesbertaglia/instagram-disclosure-trends
cd instagram-disclosure-trends

  2. Install dependencies using Poetry:

    poetry install

  3. Activate the virtual environment:

    poetry shell

Usage

To run the main script:

python scripts/collect_data.py [OPTIONS]

Options:

  • --csv_path: Path to the dataset_accounts.csv file. Default is data/dataset_accounts.csv.
  • --skip_collection: If passed, data collection will be skipped.
  • --skip_create_df: If passed, processing the raw CrowdTangle data into a DataFrame will be skipped.
  • --skip_augmentation: If passed, augmenting the DataFrame with additional columns will be skipped. Use this option for collecting data from new accounts not included in the original dataset.
  • --post_df_path: Path to the processed posts df pickle file. Default is data/df_posts.pkl.
  • --profile_df_path: Path to the processed profiles df pickle file. Default is data/df_profiles.pkl.

Troubleshooting

  • Ensure that the .env file exists in the root directory with the correct API_TOKEN.
  • Verify that the CSV file provided contains all the necessary columns.

License

MIT

Contact

For any queries or issues, please contact Thales Bertaglia.