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The Human RFID Implants Introduce a New Level of Human-Computer Interaction: Twitter Topic Detection Gauges Consumer Opinions

EasyChair Preprint no. 9679, version 2

Versions: 12history
12 pagesDate: May 3, 2023

Abstract

Human subcutaneous implants are being made available as the new level of human-computer interaction as well as a convenient way to streamline everyday routines. The reception of this new idea is varied: in Sweden it is possible to pay train fares with implanted chip vs. in the USA some states are using legislation to ensure that residents cannot be implanted without their consent. Despite the resistance to this application of technology, the signs for major digital transformation are already evident. Industries like banking, health care and security should be closely monitoring the development opportunities implanted devices offer.

The microblogging site Twitter has been linked to the younger, more affluent, and pro-technology users. This makes Twitter feed an excellent opportunity to gauge population opinions regarding human subcutaneous chip implants. The KNIME software was used for unsupervised topic detection with Latent Dirichlet Allocation (LDA) algorithm to identify six key issues engaging tweeting public.

Keyphrases: Human chipping, KNIME, machine learning, RFID, Subcutaneous implant, text mining, topic detection, Twitter

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:9679,
  author = {Outi Niininen and Stephen Singaraju and Luis Arango},
  title = {The Human RFID Implants Introduce a New Level of Human-Computer Interaction: Twitter Topic Detection Gauges Consumer Opinions},
  howpublished = {EasyChair Preprint no. 9679},

  year = {EasyChair, 2023}}
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