Researchers from the University of Central Florida (UCF) have developed a sarcasm detector for social media platforms using artificial intelligence.
According to Ramya Akula, sarcasm in face-to-face interactions is easier to determine, one of the researchers of the study.
However, the lack of facial expressions and vocal tones in Facebook posts and Tweets makes it more tedious to catch. What more, if a computer attempts to figure it out.
"Sarcasm detection in online communications from social networking platforms is much more challenging," Ramya said, though UCF's website.
The social measures brought upon the Covid 19 pandemic have forced most people to interact online. Therefore, companies are also obliged to follow their customers to continue showcasing their products and services. And to further improve their relationship with clients, they will have to collect and observe the latter's feedback.
However, sarcasm may ruin proper sentiment analysis-the method of identifying customer's emotions. Thankfully, a group of computer science researchers from UCF has developed an answer to this dilemma.
The findings, published in Entropy, developed a computer model finding indications of sarcasm through cue words, UCF said on its website.
How Does It Detect Sarcasm?
As mentioned earlier, catching sarcastic tones is tedious, even for people. So how was artificial intelligence successful enough to do so?
The cue words placed in a specific combination could say that a social media post has hints of sarcasm. They based the finding on posts on Twitter and Reddit. The researchers also studied the headlines of The Onion, a digital satirical publication. In addition, it was a result of relating keywords to other words.
It turns out that there are frequently used words for ironic mockery. It includes: "just," "again," "totally," and even the exclamation point Ramya revealed to Defense One.
According to Ramya Akula, one of the researchers, the said words have "darker edges connecting them with every other word in a sentence." He also added that these words -- aside from their usual presence in sarcasm -- received more attention from the computer model.
Moreover, the researchers used an attention mechanism to identify patterns in sarcastic texts, Ivan Garibay, one of the researchers, said to Defense One.
Hence, the developed algorithm will help brands get a more accurate picture of how their customers feel. A sarcastic review of a business' service or product will no longer be filed under positive reviews.
Other Similar Studies
The research may sound familiar to some. It is because other researchers have also attempted to decipher sarcasm through A.I. before.
However, it is noteworthy that the present study is a significant improvement from before. It is because former algorithms were trying to look for multiple cues that even included emojis.
In January 2016, researchers from Carnegie Mellon University attempted to train computers to identify sarcastic Tweets. Interestingly, their findings used the lack of mutual friends in mentions as one of the sarcasm indicators.
Back in June 2014, even the United States Secret Service was reportedly attempting to purchase software that could detect sarcasm on social media. Their objective was to automate the monitoring process of social media accounts.
This article is owned by Tech Times
Written by Teejay Boris
