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Social media data use

  • 26 Jul 2021 07:41
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The award will create opportunities for him to research potential applications for the vast amounts of data generated by social media networks. These include:

  • identifying interest groups which could be targeted for particular purposes, such as health campaigns
  •  categorising network users based on  influence or importance, rather than purely overall bandwidth
  • predicting energy usage of individual households, to estimate future demand and minimise waste.

“There is a wealth of data created through digital channels such as text messages, tweets and on-line shopping, " says Professor Higham "People can belong to different networking communities at different times depending on their circumstances - for example, related to work, family or hobbies.

“Analysis of this information is challenging because the data sets are massive and they change rapidly. For example, a live event or a breaking news item can involve thousands of new messages per minute, touching millions of accounts. And they can generate ‘spikes of sentiment’, with positive or negative reactions to a sudden or unexpected occurrence.

“In this project, we’ll be developing tools to compare and categorise dynamic networks, identifying social media communities that emerge and disperse and assessing which parts of the network play crucial roles in disseminating information.

“One application of this work is in health informatics, to determine whether people affected by specific diseases such as diabetes or asthma form closely-knit online communities or are spread arbitrarily throughout cyberspace. Exploiting this information could help us to disseminate messages, news and advice more effectively to these groups.”

Professor Higham’s project builds on work he has carried out with Leeds-based digital advertising agency Bloom Media, which has led to measurements of online influence in large-scale Twitter conversations.

Funded by the Leverhulme Trust, the Senior Research Fellowship scheme is designed for scientists who would benefit from a period of full-time research without teaching and administrative duties. The scheme reimburses the employing institution with the full salary cost of a teaching replacement. 

Below. Courtesy: http://www.dos-rios.com/


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