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Aspect-Based Extraction and Analysis of Affective Knowledge from Social Media Streams

By Lori Cameron

By Lori Cameron on
July 28, 2017

tablet with connected peopletablet with connected peopleHow are You Feeling? Big Corporations Want to Know

You might remember the Volkswagen emissions scandal from 2015 where Volkswagen was charged with violating clean air standards in cars they sold from 2008 to 2015. The company built emissions systems designed to pass emissions testing but that emitted up to 40 times more nitrous oxides into the air otherwise.

Companies hate these kinds of scandals because they can injure a brand name and cut into profits for years. Companies that want to recover from such bad publicity need to pay attention to social media streams and the information they reveal about how the public feels about the scandal.

Researchers who analyzed Internet chatter about the Volkswagen scandal found that while the predominant feeling toward the company was negative, consumers still had positive things to say about VW’s gearbox and seat quality.

It takes a sophisticated algorithm to extract and analyze communications for this kind of information. Yet, companies need and want this information so they can plan and evaluate their corporate communications campaigns.

Read more about how researchers are developing better methods for mining public knowledge bases to analyze consumer emotion in the May/June 2017 issue of IEEE Intelligent Systems.

Read article (login may be required for full text)


About Lori Cameron

Lori Cameron is a Senior Writer for the IEEE Computer Society and currently writes regular features for Computer magazine, Computing Edge, and the Computing Now and Magazine Roundup websites. Contact her at l.cameron@computer.org. Follow her on LinkedIn.

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