{"id":63429,"date":"2024-07-15T12:26:24","date_gmt":"2024-07-15T12:26:24","guid":{"rendered":"https:\/\/mention.com\/?p=63429"},"modified":"2024-11-13T09:10:50","modified_gmt":"2024-11-13T09:10:50","slug":"ai-at-mention","status":"publish","type":"post","link":"https:\/\/mention.com\/en\/blog\/ai-at-mention\/","title":{"rendered":"AI: An Ongoing Journey at Mention\u00a0"},"content":{"rendered":"\n

12 Years at the Forefront of Artificial Intelligence<\/strong><\/h2>\n\n\n\n

Since our launch 12 years ago, Mention has consistently integrated AI to both enhance the user experience and simplify the resolution of our customer’s pain points.

For us, artificial intelligence has been the cornerstone of our product for years, not just a marketing trend to surf on. <\/p>\n\n\n\n

Let’s look back together.<\/p>\n\n\n\n

Sentiment Analysis – 2013<\/h3>\n\n\n\n

It was only a year after launching our service that we realized the importance of Sentiment monitoring. It wasn’t just about collecting mentions, it was about making them meaningful and translating their feelings (positive\/negative\/neutral) into valuable insights for customers.<\/p>\n\n\n\n

We represented the sentiment of a mention with a green\/grey\/red color code, as you can see below.
<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

At the time, we were one of the few players in the market to offer this functionality. Since then, we’ve published no less than four versions of Sentiment Analysis, the latest of which was released in June 2024. <\/p>\n\n\n\n

But let’s have Bryan explain the latest changes!
The architecture of Sentiment Analysis dated back to 2017, and we felt we needed to bring it up to date in light of technical advances in NLP (<\/em>Natural Language Processing<\/em><\/a>) and machine computing capabilities. <\/em><\/p>\n\n\n\n

The model we built is based on the <\/em>Transformers architecture <\/em><\/a>(similar to ChatGPT).

Our first step was to pre-train it on 2.5TO of data and on 100 different languages so that it understands the grammar and spelling of all the different languages. But that was not enough! Our model needed to work on sentiment classification. <\/em><\/p>\n\n\n\n

We fine-tuned the model by gathering a pool of 500k mentions and asking it to classify between positive\/negative\/or neutral. <\/em><\/p>\n\n\n\n

The result lived up to my expectations, with an accuracy rate of 82% on the 5 main languages. <\/em><\/p>\n\n\n\n

My next step will be to focus my energy on a new project: <\/em>emotion analysis <\/em><\/a>where I\u2019m going to classify mentions based on Anger, Joy, Sadness\u2026
<\/em>Bryan Sichoix – Machine Learning Engineer <\/strong><\/a>@Mention
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Pulse Email – 2015<\/h3>\n\n\n\n

Given the success of the Sentiment analysis feature, our technical team continued their investigations in the AI field.<\/p>\n\n\n\n

Collecting mentions, being able to categorize them automatically, and knowing the sentiment was already a good foundation. Still, the sheer volume of data meant that we could offer customers even more, especially those facing crisis, by alerting them in real time to unexpected changes in data volume. Thus, a new use-case was born: Crisis Management. <\/p>\n\n\n\n

\"Pulse<\/figure>\n\n\n\n

\u201cWe’re really talking about basic artificial intelligence here, but artificial intelligence nonetheless. In practice, it’s pretty straightforward: by creating alerts, customers collect mentions. The more you collect, the more you have. The more data you have, the better you are able to spot trends and anomalies in those trends. <\/em><\/p>\n\n\n\n

That’s Pulse: the ability to alert our customers by email when an anomaly in the volume of mentions is detected.\u201d<\/em><\/p>\n\n\n\n

Andrey Virodov<\/strong> – Lead Dev <\/strong><\/a>@Mention<\/p>\n\n\n\n

Want to know more about the Pulse email (now \u2018Spike\u2019 email)? Check out this article<\/a>.<\/p>\n\n\n\n

If there’s one thing we can be sure of, it’s that since these early developments, technological advances have enabled AI to be widely adopted. And that’s precisely what we’re building for our customers right now. <\/p>\n\n\n\n

So, let\u2019s go over the latest developments.<\/p>\n\n\n\n

A few months of focus, a few months of success <\/h2>\n\n\n\n

Yes, the title may seem a little presumptuous, but objectively speaking, we have to admit that our product and tech teams have spoiled us recently with the recent releases:<\/p>\n\n\n\n