DOI: 10.5281/zenodo.17563499
title: Professional ATP Tennis Players Instagram dataset for engagement research

description: This dataset was developed to study user engagement on Instagram posts of ATP Tennis Players. Information was retrieved both from the official ATP website and Instagram for 341 tennis players whose Instagram public accounts were identified, and had a position in the ATP Ranking during 2024. The final sample consists of 4,451 English-written posts published by these users throughout the year 2023. Data was downloaded using Web Scraping with Python. 

The variables in the dataset are described as follows:



id: entry identificator;



username: Instagram username;




shortcode:  Instagram post identifier;




date: YYYY-MM-DD;




timestamp: HH:mm:ss UTC




video: binary for post containing video;




likes: number of likes of the post at the moment of download;




comments: number of comments of the post at the moment of download;




is_sponsored: binary for post being sponsored;




sponsors: sponsor of the post;




text_detected: binary for text detected in the image;




type: binary for tennis instruments detected in the image;




faces: number of faces detected in the image;




emotion: emotion detected in the faces of the image (Happiness, Sadness, Fear, Anger, Surprise, Disgust and Neutrality);




points: ATP points of the player at the moment of download;




monetary_prize: monetary prize collected by the player in the ATP tournaments;




age: age of the player;




player brands: brands that appear at the ATP official website sponsoring the player;




Nike: binary for Nike being a sponsor of the player;




Wilson: binary for Wilson being a sponsor of the player;




Yonex: binary for Yonex being a sponsor of the player;




Adidas: binary for Adidas being a sponsor of the player;




Asics: binary for Asics being a sponsor of the player;




Head: binary for Head being a sponsor of the player;




Australian_Open: binary for post published during the Australian Open (12 – 26 January 2023);




Roland_Garros: binary for post published during Roland Garros (25 May – 8 June 2023);




Wimbledon: binary for post published during Wimbledon (30 June – 13 July 2023);




US_Open: binary for post published during the US Open (24 August – 7 September 2023);




time_slot: it indicates the time slot of the day when the post was published: in the morning, in the afternoon, or at night. The morning time slot is considered to be between 5:00 AM and 12:59 PM. The afternoon time slot is considered to be between 1:00 PM and 8:59 PM. Finally, the night time slot is considered to be between 9:00 PM and 4:59 AM. The Spanish time zone was used as a reference, but this does not guarantee that the post was published in the same time slots, since the publication time may differ depending on the user's geographic location;




weekend: binary for post being published during the weekend;




num_hashtags: number of hashtags in the post caption;




num_mentions: number of mentions in the post caption;




num_emojis: number of emojis in the post caption;




language: language in which the post was written;




word_count: number of words of the caption;




posts: number of posts published by the player on the Instagram account at the moment of download;




followers: number of Instagram followers of the player at the moment of download;




following: number of Instagram followed accounts by the player at the moment of download;



The following variables are organized into a wide range of linguistic categories, classified according to a percentage system based on the total number of words in the text using LIWC-22 (https://www.liwc.app/help/psychometrics-manuals):





segment;




WC;




Analytic;




Clout;




Authentic;




Tone;




Affect;




tone_pos;




tone_neg;




emotion;




emo_pos;




emo_neg;




emo_anx;




emo_anger;




emo_sad;




swear:




Social;




socbehav;




prosocial;




polite;




conflict;




moral;




comm;




socrefs;




family;




friend;




female;




male;




Culture;




politic;




ethnicity;




tech;




Lifestyle;




leisure;




home;




work;




money;




relig;




Physical;




health;




illness;




wellness;




mental;




substances;




sexual;




food;




death;



The file is csv formatted, and the columns are separatad by semicolon.