Twitter Accounts Suggestion: Pipeline Technique SpaCy Entity Recognition

Shabbab Algamdi, Abdullah Albanyan, Sayed Khushal Shah, Zeenat Tariq

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Twitter Accounts Suggestion is concerned with recommending accounts for the users according to their tweet contents. Twitter contains a massive amount of data that can be useful for knowing each user's preferences. This paper uses Named Entity Recognition (NER), one of the techniques used in Natural Language Processing (NLP). We propose a pipeline technique to analyze the textual content of tweets to recommend the proper user accounts (people or organizations) to facilitate mentioning other user accounts in the tweets.

Original languageEnglish
Title of host publicationProceedings - 2022 IEEE International Conference on Big Data, Big Data 2022
EditorsShusaku Tsumoto, Yukio Ohsawa, Lei Chen, Dirk Van den Poel, Xiaohua Hu, Yoichi Motomura, Takuya Takagi, Lingfei Wu, Ying Xie, Akihiro Abe, Vijay Raghavan
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5121-5125
Number of pages5
ISBN (Electronic)9781665480451
DOIs
StatePublished - 2022
Externally publishedYes
Event2022 IEEE International Conference on Big Data, Big Data 2022 - Osaka, Japan
Duration: 17 Dec 202220 Dec 2022

Publication series

NameProceedings - 2022 IEEE International Conference on Big Data, Big Data 2022

Conference

Conference2022 IEEE International Conference on Big Data, Big Data 2022
Country/TerritoryJapan
CityOsaka
Period17/12/2220/12/22

Keywords

  • Accounts
  • Named Entity Recognition
  • Natural Language Processing
  • Recommendation
  • Twitter

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