Sentiment Analysis With NLP: A Catalyst for Sales in Analyzing the Impact of Social Media Ads and Psychological Factors Online

Sentiment Analysis With NLP: A Catalyst for Sales in Analyzing the Impact of Social Media Ads and Psychological Factors Online

DOI: 10.4018/979-8-3693-5288-5.ch008
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Abstract

This chapter explores the role of sentiment analysis, powered by NLP, in boosting sales amidst “Intersection of AI and Business Intelligence in Data-Driven Decision-Making.” It analyzes how social media ads and psychological factors shape online shopping behavior, demonstrating how sentiment analysis drives digital commerce sales. Sentiments from platforms like Twitter, Facebook, and Instagram are categorized into positive, negative, or neutral using advanced NLP algorithms. The chapter delves into psychological factors such as trust, credibility, brand perception, and emotional responses triggered by social media ads. Through sentiment analysis, patterns and correlations between sentiment expressions and consumer actions are revealed, illuminating the impact of social media advertising on online shopping behavior. This insight aids marketers in optimizing digital strategies, developing effective campaigns to enhance sales performance, and engaging customers in the online shopping domain.
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