Analyzing user sentiment in social media: Implications for online marketing strategy

Micu, Adrian; Micu, Angela-Eliza; Geru, Marius; Lixăndroiu, Radu

doi:10.1002/mar.21049

Cited by 85 publications

(42 citation statements)

References 28 publications

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“…As mentioned previously, event outcomes refer to the observed firm performance during customers’ brand- or firm-related interactions. We focus on individuals’ experiential interactions with a firm or brand, consistent with research on service encounters (Micu et al 2017), and postconsumption product perceptions (Babić Rosario et al 2016). While overall satisfaction (Farhadloo, Patterson, and Rolland 2016; He et al 2016; Misopoulos et al 2014) and brand perceptions (Schweidel and Moe 2014) reflect customers’ experiences, these concepts are often broader, reflecting a series of interactions or experiences.…”

Section: Conceptual Frameworkmentioning

confidence: 99%

The Role of Marketer-Generated Content in Customer Engagement Marketing

Meire¹,

Hewett²,

Ballings³

et al. 2019

Journal of Marketing

193

154

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Despite the demonstrated importance of customer sentiment in social media for outcomes such as purchase behavior and of firms’ increasing use of customer engagement initiatives, surprisingly few studies have investigated firms’ ability to influence the sentiment of customers’ digital engagement. Many firms track buyers’ offline interactions, design online content to coincide with customers’ experiences, and face varied performance during events, enabling the modification of marketer-generated content to correspond to the event outcomes. This study examines the role of firms’ social media engagement initiatives surrounding customers’ experiential interaction events in influencing the sentiment of customers’ digital engagement. Results indicate that marketers can influence the sentiment of customers’ digital engagement beyond their performance during customers’ interactions, and for unfavorable event outcomes, informational marketer-generated content, more so than emotional content, can enhance customer sentiment. This study also highlights sentiment’s role as a leading indicator for customer lifetime value.

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Section: Conceptual Frameworkmentioning

confidence: 99%

The Role of Marketer-Generated Content in Customer Engagement Marketing

Meire¹,

Hewett²,

Ballings³

et al. 2019

Journal of Marketing

193

154

View full text Add to dashboard Cite

show abstract

“…particular topic such as a brand, or organization. For example, Micu et al (2017) discuss the use of sentiment analysis in understanding the valence of social media posts and its role in the development of online marketing strategy.…”

Section: The Search Terms Definedmentioning

confidence: 99%

“…Sentiment analysis refers to the process of using a computer to identify and categorize the tone expressed in a piece of text, usually to determine the valence of the author’s attitude towards a particular topic such as a brand, or organization. For example, Micu et al (2017) discuss the use of sentiment analysis in understanding the valence of social media posts and its role in the development of online marketing strategy.…”

Section: The Search Terms Definedmentioning

confidence: 99%

Artificial intelligence in marketing: A bibliographic perspective

Feng

Park

Pitt

et al. 2020

Australasian Marketing Journal

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The concept of artificial intelligence (AI) was born in the mid-twentieth century to describe endeavours in computer science focusing on the simulation of human learning. Since then, advances in computing, data collection and data storage have made AI an increasingly important area for researchers and practitioners across a range of disciplines in business and the social sciences. Despite that, there appears to be very few attempts at cataloging and condensing prior research in this area. As such, this paper uses the VOSViewer data visualizer to determine the major authors in the field and to identify themes and concepts emanating from prior research.

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“…TextBlob is a Python (2 and 3) library for processing textual data. Micu et al [46] employed TextBlob to analyze customers' liking, rating and reviewing restaurants. They found that TextBlob is an effective tool sentiment analysis tool.…”

Section: Sentiment Analysismentioning

confidence: 99%

Public Opinions about Online Learning during COVID-19: A Sentiment Analysis Approach

Bhagat

Mishra²,

Dixit

et al. 2021

Sustainability

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The aim of this study was to analyze public opinion about online learning during the COVID-19 (Coronavirus Disease 2019) pandemic. A total of 154 articles from online news and blogging websites related to online learning were extracted from Google and DuckDuckGo. The articles were extracted for 45 days, starting from the day the World Health Organization (WHO) declared COVID-19 a worldwide pandemic, 11 March 2020. For this research, we applied the dictionary-based approach of the lexicon-based method to perform sentiment analysis on the articles extracted through web scraping. We calculated the polarity and subjectivity scores of the extracted article using the TextBlob library. The results showed that over 90% of the articles are positive, and the remaining were mildly negative. In general, the blogs were more positive than the newspaper articles; however, the blogs were more opinionated compared to the news articles.

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Analyzing user sentiment in social media: Implications for online marketing strategy

Cited by 85 publications

References 28 publications

The Role of Marketer-Generated Content in Customer Engagement Marketing

The Role of Marketer-Generated Content in Customer Engagement Marketing

Artificial intelligence in marketing: A bibliographic perspective

Public Opinions about Online Learning during COVID-19: A Sentiment Analysis Approach

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