<abstract xmlns="http://www.w3.org/1999/xhtml">

<underline>Purpose.</underline> Microblogging sites are being used by people across the globe to share their opinions and to express sentiments for everything in real time. Through social listening, companies analyse the sentiments to assess the way forward, and the researchers use it to analyse the trend or an event and give forward-looking recommendations. The objective of the paper is to analyse the sentiments of people relating to Paytm IPO which can be used to predict the way forward.
<underline>Design/methodology/approach</underline>. The study attempts sentiment analysis. For this purpose, QSR NVIVO 12, the qualitative analysis tool was used to retrieve the tweets from the Twitter website. NCapture was installed for this purpose. Post data cleaning, stemming, query augmentation and classification, the Twitter data was analysed.
<underline>Findings</underline>. The sentiments around the IPO of Paytm have been negative and sarcastic. The extremely negative tweets were near twice the number of extremely positive tweets.
<underline>Practical implication</underline>. The study can help an investor in evaluating the investment that they might be planning in the given company. For the company, whose IPO is being considered, an analysis of the sentiments around the IPO can help in taking corrective measures, if the sentiment is negative, towards reputation building.
<underline>Originality/value</underline>. The study is an original contribution to the extant literature in the field of sentiment analysis.
</abstract>

Purpose. Microblogging sites are being used by people across the globe to share their opinions and to express sentiments for everything in real time. Through social listening, companies analyse the sentiments to assess the way forward, and the researchers use it to analyse the trend or an event and give forward-looking recommendations. The objective of the paper is to analyse the sentiments of people relating to Paytm IPO which can be used to predict the way forward.
Design/methodology/approach. The study attempts sentiment analysis. For this purpose, QSR NVIVO 12, the qualitative analysis tool was used to retrieve the tweets from the Twitter website. NCapture was installed for this purpose. Post data cleaning, stemming, query augmentation and classification, the Twitter data was analysed.
Findings. The sentiments around the IPO of Paytm have been negative and sarcastic. The extremely negative tweets were near twice the number of extremely positive tweets.
Practical implication. The study can help an investor in evaluating the investment that they might be planning in the given company. For the company, whose IPO is being considered, an analysis of the sentiments around the IPO can help in taking corrective measures, if the sentiment is negative, towards reputation building.
Originality/value. The study is an original contribution to the extant literature in the field of sentiment analysis.

Social Listening Through Sentiment Analysis of Twitter Data: A Case Study of Paytm IPO

Associate Professor, Department of Commerce

Shaheed Bhagat Singh College, University of Delhi

Professor, Department of Commerce, Shaheed Bhagat Singh College

Associate Professor, Department of Commerce, Shaheed Bhagat Singh College

SocioEconomic Challenges (SEC)

This work is licensed under the Creative Commons Attribution 4.0 International License.

Purpose. Microblogging sites are being used by people across the globe to share their opinions and to express sentiments for everything in real time. Through...

Social Listening Through Sentiment Analysis of Twitter Data: A Case Study of Paytm IPO

Publicado en línea: 29 oct 2022

Páginas: 39 - 47

Recibido: 13 jul 2022

Aceptado: 29 ago 2022

DOI: https://doi.org/10.21272/sec.63.39-47.2022

Palabras clave
social media, Twitter data, sentiment analysis, opinions, tweets

© 2022 Meera Mehta et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Social Listening Through Sentiment Analysis of Twitter Data: A Case Study of Paytm IPO

Publicado en línea: 29 oct 2022

Páginas: 39 - 47

Recibido: 13 jul 2022

Aceptado: 29 ago 2022

DOI: https://doi.org/10.21272/sec.63.39-47.2022

Palabras clavesocial media, Twitter data, sentiment analysis, opinions, tweets

© 2022 Meera Mehta et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Palabras clave
social media, Twitter data, sentiment analysis, opinions, tweets