Measuring Word of Mouth in Real-Time: A Study of “Tweets” and Their Dynamic Relation to Movie Sales and Marketing Efforts.
(2010)Department of Business Administration
- Abstract
- Thesis Purpose: This study aims to test whether electronic word-of-mouth in the form of comments on twitter are representative of overall word-of-mouth. The relationship between marketing, twitter comments, sales is tested and compared to word-of-mouth theory and previous studies. Methodology: A combination of cross-sectional research and case study research methodologies were used to understand Twitter messages using primarily quantitative analysis which was supplemented with qualitative analysis where appropriate to understand word of mouth on Twitter and its relationship with existing word of mouth theory. Theoretical perspective: The main theories that the study is based upon are theory concerning word-of-mouth and electronic... (More)
- Thesis Purpose: This study aims to test whether electronic word-of-mouth in the form of comments on twitter are representative of overall word-of-mouth. The relationship between marketing, twitter comments, sales is tested and compared to word-of-mouth theory and previous studies. Methodology: A combination of cross-sectional research and case study research methodologies were used to understand Twitter messages using primarily quantitative analysis which was supplemented with qualitative analysis where appropriate to understand word of mouth on Twitter and its relationship with existing word of mouth theory. Theoretical perspective: The main theories that the study is based upon are theory concerning word-of-mouth and electronic word-of-mouth. Empirical data: The empirical data consist of approximately three million comments from twitter.com, box-office data and marketing information concerning 14 movies. Conclusions: Twitter can accurately represent the overall population’s WoM for the movie industry and accurately models the relationships between sales, marketing and word of mouth according to WoM theory. This study further demonstrates a practical method for monitoring word of mouth in real time and creates models that could be used to predict future outcomes. Furthermore, the study contributes to existing theory by helping to bridge the gap in understanding the difference between eWoM and traditional WoM by proving that the fundamental effects of WoM whether it is online or offline are the same. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/1626974
- author
- Parrot, Kim and Ohashi, Kevin
- supervisor
- organization
- year
- 2010
- type
- H1 - Master's Degree (One Year)
- subject
- keywords
- Word-of-mouth, sentiment, twitter, marketing, sales, Management of enterprises, Företagsledning, management
- language
- Swedish
- id
- 1626974
- date added to LUP
- 2010-06-02 00:00:00
- date last changed
- 2012-04-02 18:04:20
@misc{1626974,
abstract = {{Thesis Purpose: This study aims to test whether electronic word-of-mouth in the form of comments on twitter are representative of overall word-of-mouth. The relationship between marketing, twitter comments, sales is tested and compared to word-of-mouth theory and previous studies. Methodology: A combination of cross-sectional research and case study research methodologies were used to understand Twitter messages using primarily quantitative analysis which was supplemented with qualitative analysis where appropriate to understand word of mouth on Twitter and its relationship with existing word of mouth theory. Theoretical perspective: The main theories that the study is based upon are theory concerning word-of-mouth and electronic word-of-mouth. Empirical data: The empirical data consist of approximately three million comments from twitter.com, box-office data and marketing information concerning 14 movies. Conclusions: Twitter can accurately represent the overall population’s WoM for the movie industry and accurately models the relationships between sales, marketing and word of mouth according to WoM theory. This study further demonstrates a practical method for monitoring word of mouth in real time and creates models that could be used to predict future outcomes. Furthermore, the study contributes to existing theory by helping to bridge the gap in understanding the difference between eWoM and traditional WoM by proving that the fundamental effects of WoM whether it is online or offline are the same.}},
author = {{Parrot, Kim and Ohashi, Kevin}},
language = {{swe}},
note = {{Student Paper}},
title = {{Measuring Word of Mouth in Real-Time: A Study of “Tweets” and Their Dynamic Relation to Movie Sales and Marketing Efforts.}},
year = {{2010}},
}