If you are living in this modern era, you must be familiar with how people, especially the young generation, are associated with AI, or artificial intelligence, for their day-to-day work. Not only does it help in work, AI also plays the role of a mentor and a friend. Many people have befriended AI for sharing their regular thoughts, ideas and emotions.
In the digital age, to express emotions, face-to-face interactions are no longer the obligatory requirement; it can be expressed through online texts and other digital forms. In this regard, sentiment analysis, a subset of natural language processing (NLP), has emerged as a powerful tool to understand and identify emotions in text. It is designed to analyze whether the tone of a text is positive, negative or neutral by utilizing AI. It uses tools like algorithms and machine learning for the procedure.
The Power of Sentiment Analysis
This innovation is providing valuable insights for every field, including businesses, researchers, marketers, etc.
- Business and Customer Service: Companies use sentiment analysis in order to expand their business. By utilizing it, they understand the feelings of customers regarding their services. Companies analyze reviews and feedback so that they can understand what customers like or dislike. Through this procedure, companies fix the flaws and improve their services.
- Education: Sentiment analysis is really helpful in updating the educational policies. By understanding student feedback, educators can improve teaching methods, adjust curriculum content, and address concerns to enhance learning experiences, regardless of the education levels.
- Mental Health: In the healthcare sector, sentiment analysis is used to identify early signs of mental health problems. By analyzing texts, it can identify if the user is suffering from anxiety or depression. This helps doctors or therapists to take immediate actions to support those in need.
- Tourism and Hospitality: Hotels, airlines, and travel companies that are associated with tourism and hospitality utilize sentiment analysis to analyze customer reviews. This helps them improve service quality.
- Entertainment and Media: Sentiment analysis is greatly used in the entertainment industry. By employing it, they get to understand audience reactions to movies, TV shows or music. As a result, creators or makers get to adjust their content and attract more viewers.
These are only a few examples of the power of sentiment analysis. There are many more sectors where it is used for benefits.
The Limitations of Sentiment Analysis
No matter how much power AI sentiment analysis holds, it has some vital limitations. AI sentiment analysis sometimes lags behind when it comes to truly understanding the complexities of human emotions.
- Emotions can’t be Easily Categorized: Human beings go through a lot of mixed emotions, which are not often comprehensible by sentiment analysis tools. Human emotions can’t just be categorized into positive, negative or neutral. We, in a single sentence, can express more than one emotion, which seems to be hard to get for AI.
- Ambiguous Language: Humans often use language that is not clear, kind of vague. For instance, a person can fiercely write okay or fine, but the sentiment analysis models will take it as merely a positive response.
- Hardship with Context: One of the biggest challenges sentiment analysis tools face is understanding context. We often use words that can have separate meanings. The meaning completely depends on the situation in which they are used. As a result, sentiment analysis sometimes offers inaccurate interpretations.
- Can’t Identify Sarcasm: Another challenge in sentiment analysis is identifying sarcasm and irony. People, especially in this modern era, love to use sarcastic and ironic words or statements to convey emotions. It means the emotion can be the opposite of the actual meaning of the used statement. AI often fails to recognize the settings.
- Cultural and Linguistic Differences: Every language and every culture has its distinct way to express emotion. Therefore, sentiment analysis tools trained in a particular language or culture can’t properly analyze emotion in another. The minority language users especially face a lot of difficulties because of this.
- Lack of Empathy: Sentiment analysis tools are designed to analyze the emotional tone of a text, but they lack empathy in their response. As a result, if a person in a vulnerable situation seeks to get emotional support from AI, the consequence sometimes turns dangerous.
Though sentiment analysis still exhibits some flaws, the future looks promising as AI and natural language processing technologies are evolving. Researchers and technicians are working on improving algorithms so that AI can understand human emotions more accurately.
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Writer
Kazi Mirana Mainuddin
Intern, Content Writing Department
YSSE