Deep Learning based Sentiment Analysis on Images

Abstract

Sentiment analysis is a powerful tool that has been gaining popularity among businesses in recent years. It involves analyzing text, speech, or images to understand the emotions or opinions conveyed by them. This process can provide valuable insights into customer preferences, behavior, and satisfaction levels. By leveraging sentiment analysis, businesses can gather customer feedback on their products and services, which can help them identify areas for improvement and develop stronger customer relationships. Furthermore, sentiment analysis can also be used to support emotional marketing campaigns, allowing businesses to create more targeted and personalized messaging that resonates with their audience. For example, by analyzing social media posts and comments, businesses can gain a better understanding of how their brand is perceived and adjust their marketing strategies accordingly. One popular method for this is transfer learning, where pre-trained models are used to analyze new datasets. Deep learning algorithms, such as convolutional neural networks (CNNs), have been particularly successful in achieving accurate results in a variety of applications, including image sentiment analysis. However, analyzing emotions conveyed through images is a complex task, and there is still much room for improvement. The Inception-v3 technique is a notable development in this field, as it can easily identify key parts of the body, such as the face, which is essential for accurately detecting emotions. The results of this model were compared to those of various other machine learning approaches, and the suggested model showed superior accuracy levels of up to 99.5%. This research demonstrates the potential of using deep learning algorithms and transfer learning methods to improve image sentiment analysis. For example, in the field of Healthcare, image sentiment analysis can be used to detect emotional expressions of patients, which can be valuable for assessing their mental and emotional state. In Sales and Marketing, it can be used to evaluate customers' emotional responses to different products or campaigns, allowing businesses to tailor their strategies accordingly. Overall, the use of image sentiment analysis can provide valuable insights to businesses across a wide range of industries.