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PR, Big Data and the Semantic Web

PR, Big Data and the Semantic Web. A n Introduction. Grey Beards and New Technologies. David Phillips Political and corporate PR, consultancy and research, author and academic. How this is going to be hard for practitioners and entrants. Everyone . At work and play people are connected

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PR, Big Data and the Semantic Web

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  1. PR, Big Data and the Semantic Web A n Introduction

  2. Grey Beards and New Technologies • David Phillips • Political and corporate PR, consultancy and research, author and academic. • How this is going to be hard for practitioners and entrants

  3. Everyone • At work and play people are connected • At the same time people are employees, consumers, activists and more. • The create and consume news created by everyone • News is re-purposed, likes shared and +’d

  4. Following the news • Radio, TV, newspapers, magazines • Facebook, Pinterest, G+, YouTube, Wiki’s and thousands of other channels. • Creators of words, photos, videos, likes and +’s • Re-tweets and shares • A mass of information

  5. Information or data • All this content and its URL’s • Site location, ownership, user demographics, date and time used, from which site to which site. • To be able to use it PR has is at a turning point. • Is this information or data

  6. Making data work for you • Traditional needs new solutions • News – in the past a taste of newspaper commentary, radio and TV. • Now the most significant information and the most banal information is in a multitude of channels.

  7. A process for management • There is the opportunity to mix and match the knowledge and experience of the practitioner. • Perspectives • What is important • What is positive What more is there to know?

  8. The code is invisible

  9. A quick look at semantics

  10. Teach software to curate

  11. Many applications

  12. A lot of ourcomes

  13. A working example

  14. PR meets Big Data and Semantics • We saw what big data looks like for the PR practitioner • We saw how we can get information and turn it into data • You learned how to inject professional insights into Big Data . • You now know how to get a competitive advantage.

  15. Brought to you by

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