Context based interesting tweet recommendation framework

Maulik Dang, Sanjay Singh

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Social media such as Twitter, Google+, Facebook, etc has an undeniable effect on the way information is stored and processed by us. The information available on the web is abound and hence it is essential to mine the important information and avoid the irrelevant details. Along with this, it is beneficial to consider information that is contextually similar to information related to a particular topic as it provides a big picture. Tweets contains keywords known as hashtags which provide useful information for the purpose of sentiment analysis, named entity recognition, event detection, etc. In this paper, we have analyzed Twitter data based on their hashtags, which is widely used nowadays. We have extracted tweets pertaining to a single keyword and to contextually similar keywords. For the purpose of finding similar words we have used word embeddings that capture contextual information successfully. We have used topic modeling to expose the latent structure of the documents based on probability distribution. The proposed framework helps user to find relevant tweets pertaining to a specific and to contextually similar hashtags.

Original languageEnglish
Title of host publication2016 IEEE Annual India Conference, INDICON 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509036462
Publication statusPublished - 31-01-2017
Event2016 IEEE Annual India Conference, INDICON 2016 - Bangalore, India
Duration: 16-12-201618-12-2016


Conference2016 IEEE Annual India Conference, INDICON 2016

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Networks and Communications
  • Instrumentation


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