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Telegram

This repository contains datasets used in our research on Telegram instant messaging service.

Published Papers:

1.

Arash Dargahi Nobari, Negar Reshadatmand, and Mahmood Neshati. “Analysis of Telegram, An Instant Messaging Service”,
In proceedings of The 26th ACM International Conference on Information and Knowledge Management (CIKM ’17), Nov 2017.

You may check the paper (PDF and Poster) for more information.

2.

Arash Dargahi Nobari, Malikeh Haj Khan Mirzaye Sarraf, Mahmood Neshati, and Farnaz Erfanian Daneshvar. “Characteristics of viral messages on Telegram; The world’s largest hybrid public and private messenger”, In Expert Systems with Applications.

You may check the paper (preprint) for more information.

Dataset

Version 1:

This version of the dataset is used in paper 1. The dataset is stored in a MySQL database, which can be downloaded from dropbox This file includes a dump of database in sql format.

There are five tables in this database:

  • posts: All of the crawled messages.
  • users: All of the users in messages (including members, groups and channels)
  • mentions: All mention relationships
  • fwds: All forward relationships
  • adv_tags: randomly selected posts and their spam or ham tag.

Version 2:

This version of the dataset is used in paper 2. Similar to V1, This dataset is a MySQL database, which can be downloaded from dropbox This file includes a dump of database in sql format.

Please note that this version is not augmenting version 1, and contains completely different messages, users, and information.

There are five tables in this database:

  • channels: Username and other information related to all channels in our dataset.
  • posts: All of the crawled messages.
  • tags: A list of 24 categorical tags of the messages.
  • super_tags: Parent categories for the aforementioned tags.
  • viral_messages: Viral messages including their sentiment and category tags.

Citation

Please cite the paper, If you used the data in this repository.

1.

@inproceedings{DargahiNobari:2017:ATI:3132847.3133132,
 author = {Dargahi Nobari, Arash and Reshadatmand, Negar and Neshati, Mahmood},
 title = {Analysis of Telegram, An Instant Messaging Service},
 booktitle = {Proceedings of the 2017 ACM on Conference on Information and Knowledge Management},
 series = {CIKM '17},
 year = {2017},
 isbn = {978-1-4503-4918-5},
 location = {Singapore, Singapore},
 pages = {2035--2038},
 numpages = {4},
 url = {http://doi.acm.org/10.1145/3132847.3133132},
 doi = {10.1145/3132847.3133132},
 acmid = {3133132},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {classification, instant messaging, pagerank, spam detection, telegram},
} 

2.

@article{DARGAHINOBARI2020114303,
title = "Characteristics of viral messages on Telegram; The world’s largest hybrid public and private messenger",
journal = "Expert Systems with Applications",
pages = "114303",
year = "2020",
issn = "0957-4174",
doi = "https://doi.org/10.1016/j.eswa.2020.114303",
url = "http://www.sciencedirect.com/science/article/pii/S0957417420310010",
author = "Arash {Dargahi Nobari} and Malikeh {Haj Khan Mirzaye Sarraf} and Mahmood Neshati and Farnaz {Erfanian Daneshvar}",
keywords = "Telegram, Instant messaging, Sentiment analysis, Social sensing, Viral message"
}

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