{"id":2016,"date":"2019-10-18T02:20:15","date_gmt":"2019-10-18T02:20:15","guid":{"rendered":"http:\/\/kusuaks7\/?p=1621"},"modified":"2024-03-11T15:06:55","modified_gmt":"2024-03-11T15:06:55","slug":"natural-language-processing-and-affective-computing","status":"publish","type":"post","link":"https:\/\/www.experfy.com\/blog\/ai-ml\/natural-language-processing-and-affective-computing\/","title":{"rendered":"Natural language processing and affective computing"},"content":{"rendered":"\t\t
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\n\t\t\t\t\t\t\t\t\tWhat are the natural extensions of machine learning (ML) and deep learning as well as natural language processing (NLP) and affective computing (AC)?\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tBut the subject of emotions is a pertinent one as it defines most of our decisions. Recent advances in social cognitive neuroscience and behavioural science now prove that rationality is only one of the governing principles in decision making. We are also affected by moods and consult our \u2018gut feeling\u2019 about an investment. If we were ruled by pure reason, then why would we engage in charity and philanthropy?\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tEmotions and language, which are one of the ways in which we convey emotions, thus play an important role in the way investment decisions are executed. Owing to this, considerable progress has been made in recent years in understanding the subtleties of language and emotion. These areas of study are referred to as NLP and AC respectively.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Natural language processing<\/h2><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tIn our previous research, we have largely focused on the quantitative methods of analysis. However NLP is more qualitative in nature. While quantitative data is easier to compartmentalize in the form of, say, share prices, time-series data analysis, qualitative data is harder to define and statistically model.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tFor example, when Facebook was about to become a publicly listed company in 2012, how was it that company that was\u00a0earning $1 billion in revenue<\/a>\u00a0was given a market valuation of $90 billion<\/a>? The reason for this was based on several qualitative factors such as its core ideas, its teams, and its projected potential to earn high revenue, etc. In this view, qualitative data plays an important role even in financial decisions. In fact, structured quantitative data in the form of spreadsheets and relational databases only account for\u00a020% of all available data<\/a>. The remaining 80% is in the form of social media posts (especially Twitter), images, email, text messages, audio files, Word documents, PDFs and other unstructured forms.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tTo extract insights from these unstructured sources of data, NLP uses ML and AI to understand unstructured text and provide context to language. This allows us to parse information (summarize, reduce or categorize qualitative data) being received via announcements, rumours, expert forecasts etc. in real-time and hone the decision-making process from the barrage of online information.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tIn terms of interpreting this qualitative information,\u00a0NLP can be broken down into the following sub-topics<\/a>:\n