Application of machine learning in Artificial Intelligence
Machine learning is a subfield of artificial intelligence that involves the design of problem-solving systems that are characteristic of human intelligence. Machine learning on social media helps to gain a more accurate understanding of online activities. Data also plays a major role as analysis relies on big data to get more information from social media platforms. We can use machine leaning in many ways.
Social media monitoring may be a more traditional tool for companies. It allows them to explore their online image and reputation. It can help manage conversations, that is, check social media content for trolls and business opponents. This kind of negative content is prevalent to spoil the community experience with negative messages. Such content needs to be monitored and regulated for better customer service and marketing strategy. Platforms like Twitter and Instagram have built-in analytics tools that can measure the success of past posts such as number of liked posts, clicks, comments or views. Third-party tools can provide statistical information about their audience and a similar social media understanding of the peak times they are most active on stage.
Emotion analysis or opinion is the judgment of a text. It uses tongue processing (NLP) to research social media data with predefined labels like positive, negative or neutral. Emotion analysis is used to analyze social conversations and to understand the deeper meaning that applies to a brand. Psychoanalysis can be applied on social media to gather customer support and feedback for new products.
Companies can apply emotion analysis to,
Assess a brand's reputation by understanding social sentiments.
Dealing with brand image shifts due to the rise of negative attitudes.
Understand how people feel about their competitors or industry trending topics and change the brand conversation accordingly.
Computer vision has made it possible to create a sense of content in images, that is, to identify images of brands and products without text. This is useful when customers upload photos of products without directly mentioning the merchandise name or brand. For example, if someone uploads a photo of a product saying 'Where can I buy this?', Companies can see it and send the targeted promotion to that person. If someone has a positive review for a product, the company can thank the customer for their purchase. This leads to increased interaction with the customer and increased customer loyalty. Images on social media get a higher link compared to posts with text alone. Therefore, it can be beneficial for companies to pay close attention to the people who post photos of their products. The positive engagement of companies in these photos encourages customers to post more in the future, which in turn leads to further brand promotion.
Chatbot is an AI application that mimics real conversations. They are embedded in websites or through third party messaging platforms such as direct messaging on Twitter, Facebook Messenger and Instagram. Chatbot enables companies to automate customer service by providing personalized support to customers. They address customer frustrations related to customer care support by providing standard solutions to common problems. Chatboats are more popular among young audiences as they are more likely to work for companies with a young customer base. They help save time, cost and human effort. It is very important for companies to know how customers spend time on social media platforms. Furthermore, machine learning on social media proves to be a powerful tool to help them move forward. There are a lot of conversations going on on social media for companies to manually monitor them all. Machine learning makes social media analysis more powerful and accurate.
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