Can Technology Really Understand Emotions?

    Sentiment analytics sounds complex and confusing, but what exactly  is it? Sentiment Analytics is a fancy term that means technologies attempt to understand and interpret human emotions. Reading through chapter nine, I found this idea fascinating. defines Sentiment Analytics as the following:

    “Contextual mining of text which identifies and extracts subjective information in source material, and helping a business to understand the social sentiment of their brand, product or service while monitoring online conversations.”

  Sentiment Analytics gathers consumer information from comments, reviews, media posts and articles. In the process, words are taken away to reveal their most simplified meaning. After the technology has stripped away the meaningless words, the key words left are then categorized. Although, Im sure this technology will grow and expand, currently these keywords are placed into three places depending on their translation. Positive, negative or neutral are the three places messages from consumers are placed into. How can technology decipher the words into levels of intensity or meaning?

     Sentiment Libraries are full of words, statements and dictionaries that have been manually put in beforehand. This made me appreciate the work of analytics much more, when I discovered they must do this for each language. Each language has barriers and different meanings that might not be in another language. So to adequately interpret words through the system universally, each language must be translated differently. Overtime as more and more data goes through this system, the word placements create a data chart displaying how customers feel about their company, products and services. This can be incredibly helpful  shortening the amount of time it would take to research large amounts of data.

   Are sentiment analytics really beneficial and does it accurately translate data? Sentimental Analytics can be a great resource for discovering overall customer satisfaction with a product. It also helps your business see how your brand is perceived when promoting certain things online. Sentiment analytics can be insightful into your customer service,  this information lets you know how consumers are viewing your company. It also reflects your employees’ role, and how well they are connecting to customers. As a graphic designer, I would love to better understand how my clients are viewing my work and how they perceive my design brand. Sentiment Analytics is definitely something I need to look into more to optimize my design services effectiveness. I’m still curious how reliable sentiment analytics are though. According to, sentiment analytics have a fifty percent chance of accurately defining the meaning of a consumer. Problems can also arise when words like slang, irony, sarcasm and current trend words are mis-interpreted by AI. Sentiment analytics don’t always accurately reflect consumer opinions and technology always has the chance for error. Sentiment Analytics also has problems when translating different language meanings. Another common issue with these analytics is its non functionality on different domains. Sentiment Analytics is an incredibly advanced form of technology we have today, but it certainly needs to be further developed and worked on. 


One thought on “Can Technology Really Understand Emotions?

  1. I truly think science will bring us very close to creating machines that act almost one-to-one like humans. Currently, its in a very uncanny valley. We can deep fake videos and have AI recreate voices for our favorite characters. Its a crazy time. Imagining some AI that focuses on marketing sounds just as bad as Skynet.


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