amaSocial helps social media marketers, community managers, and analysts to measure social media activity on Facebook, Twitter, Instagram, and YouTube. With the help of AI technology, and especially machine learning, the service can now also analyse the sentiment of social media posts and identify emerging trends. The media update
team explains how amaSocial is utilising AI technology.
The posts that amaSocial monitors are processed by a Data Engine that uses NLP, a technology that falls within the field of AI. NLP uses the mechanics of language to sort the various parts of speech within a social post and categorise every word it contains. This allows the engine to understand the meaning and sentiment of posts.
NLP uses the mechanics of language to sort the various parts of speech within a social post and categorise every word it contains.
According to Gavin Coetzee, a representative of amaSocial, this information will be delivered to clients in a new report. “amaSocial’s new sentiment reporting provides PR and marketing agencies with insights into the positive and negative conversations surrounding their brand, giving them actionable insights for their social media campaigns,” he notes.
“Because the Data Engine automatically analyses the sentiment of posts, clients can receive their analysis immediately. This allows them to keep up with evolving consumer attitudes towards their brands on social media as it happens.”
Keeping brands in the know with machine learning
“The Data Engine does what is called ‘entity extraction’,” explains Coetzee. “It can recognise when certain people, places, events, or concepts are appearing in social media posts more frequently. The system automatically picks up these entities and notifies our clients.”
This keeps the company up to date with topics of social media discussion surrounding their businesses – from issues such as product failures to positive buzz around their brands.
Coetzee points out that both entity extraction and the accurate analysis of social media posts are made possible through the application of machine learning in the engine amaSocial uses.
Both entity extraction and the accurate analysis of social media posts are made possible through the application of machine learning.
“In-house IT developers feed the Data Engine with sets of training data that allow it to create its own algorithms for processing similar data. With these algorithms, it can recognise words and terms – or entities – it has not come across before in the social posts it processes.”
The engine can also recognise when social media users start using new variations of words, such as slang terms or shorthand words. With machine learning, the engine adds these terms to its vocabulary, allowing it to evolve as the language it processes evolves.
“The Data Engine’s development team is intricately involved in both training it and verifying its analysis at intervals. The result of this combination of human and AI capabilities is an ever-expanding AI engine that continually improves its processing accuracy.”
Processing the Big Picture with AI technology
Apart from being a forum where people can interact with one another 24 hours a day, social media is a treasure trove of data and information. amaSocial’s use of NLP and machine learning shows its value when it comes to processing these vast amounts of data. Through the application of artificial intelligence, the social media service is keeping brands closely connected to the social media universe, and how this world affects their brand.
For more information, visit amasocial.co.za
or connect with the amaSocial team on Facebook
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