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Discovery and Analysis of Social Media Data: How businesses can create customized filters to more effectively use public data
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
2018 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Upptäckt och Utvärdering av Data från Sociala Medier : Hur företag kan skapa egna filter för att bättre nyttja publik data (Swedish)
Abstract [en]

The availability of prospective customer information present on social media platforms has led to many marketing and customer-facing departments utilizing social media data in processes such as demographics research, and sales and campaign planning. However, if your business needs require further filtration of data, beyond what is provided by existing filters, the volume and rate at which data can be manually sifted, is constrained by the speed and accuracy of employees, and their digital competency. The repetitive nature of filtration work, lends itself to automation, that ultimately has the potential to alleviate large productivity bottlenecks, enabling organizations to distill larger volumes of unfiltered data, faster and with greater precision.

This project employs automation and artificial intelligence, to filter Linkedin profiles using customized selection criteria, beyond what is currently available, such as nationality and age. By introducing the ability to produce tailored indices of social media data, automated filtration offers organizations the opportunity to better utilize rich prospective data for more efficient customer review and targeting. 

Place, publisher, year, edition, pages
2018. , p. 38
Keywords [en]
automation, marketing, machine learning, artificial intelligence, Linkedin, Bing, Google, web scraping, Headless Chrome, social selling, sales prospecting
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:lnu:diva-75275OAI: oai:DiVA.org:lnu-75275DiVA, id: diva2:1214607
Educational program
Datavetenskap, kandidatprogram, 60 hp
Presentation
2018-05-29, 11:02 (English)
Supervisors
Examiners
Available from: 2018-06-07 Created: 2018-06-07 Last updated: 2018-06-07Bibliographically approved

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fulltext(2464 kB)17 downloads
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Wöldern, Lars
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf