This paper is published in Volume-4, Issue-2, 2018
Area
Machine Learning
Author
Shipra, Rahul Yadav
Org/Univ
Maharaja Agrasen Institute of Technology, Rohini, Delhi, India
Pub. Date
16 April, 2018
Paper ID
V4I2-1810
Publisher
Keywords
Twitterbot, Recurrent neural network, Python, Tensorflow, PyTeaser.

Citationsacebook

IEEE
Shipra, Rahul Yadav. Analysing Twitter Bot, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Shipra, Rahul Yadav (2018). Analysing Twitter Bot. International Journal of Advance Research, Ideas and Innovations in Technology, 4(2) www.IJARIIT.com.

MLA
Shipra, Rahul Yadav. "Analysing Twitter Bot." International Journal of Advance Research, Ideas and Innovations in Technology 4.2 (2018). www.IJARIIT.com.

Abstract

A Twitterbot is a type of bot software that controls a Twitter account via the Twitter API. The bot software may autonomously perform actions such as tweeting, retweeting, liking, following, unfollowing, or direct messaging other accounts. The automation of Twitter accounts is governed by a set of automation rules that outline proper and improper uses of automation. Proper usage includes broadcasting helpful information, automatically generating interesting or creative content, and automatically replying to users via direct message. In this paper, we are examining the automatic replies generated by a text generating machine which generates the quote to the hashtag word (prime word) sent by a sender to the bot. For training, the bot deep neural networks, more specifically RNN(Recurrent neural network) is used for which python is used as the programming environment, and Tensorflow as the machine learning library. On the sender’s side, we applied the text summarisation algorithm using PyTeaser library to detect whether the quote generated and tweeted to the sender is by the bot or any human.