In today s world of media fragmentation and online technologies available, there is an increased popularity of online users joining social networking sites. This social media online platform provides the basis for people to connect with old friend and share their everyday lives, thoughts and events between a chosen inner circles of friends. Some take the form of blogging to share their feelings in a diary like format for people to see and comment on.
The use of microblogging services has widespread by many as a forms of quick exchange of communication whereby a limited amount of characters allow the users to express their currently thoughts and feelings in a brief but yet concise way. Twitter as it currently stands is one of the most popular micro blogging sites that let users comment and engagement in the original tweet that was published by the micro blogger (or in this case, the tweeter). Comments can come in the mood of two main forms when they are tweeted. The micro blogging service Twitter has a system whereby it can detect the sentiment of a published comment by analyzing the words within the tweeter s content. This as a result can let the system aggregate the overall feelings and sentiment of a given subject by identifying the word or hash tagged content along with the remaining terms used that people have written. It is the entire content in the tweet that the system suggests through a complex algorithm that the comment is a positive (happy, good etc.) or negative (unhappy, bad etc.) sentiment.
With such a special facility of measuring micro blogging sentiments, it would be worthwhile to see the extent of what people are tweeting about certain products, or brands and link this to their overall performance of their share values. Rationalizing this idea, there is a certain amount of viable logic behind this thinking. For example, would a newly released car in the market perform so well that people would start tweeting about its qualities? In addition, would then the performance of this car generate enough sales from tweeted reviews and as a result, increase the overall share price of the car manufacturer?
As companies are becoming increasingly concerned with the fluctuation of their stock value day by day, the perceptions based on raw figures of stock price can be different or even coincide with the correlation of online twitter perceptions. A way to identify this is to see whether there are enough positive and negative sentiments to indicate a correlation between the two sources highlighting the fact that a tweeted brand may deliver sales as well as an increase in performing stock value. Thus, it would be an interesting area of research to identify whether twitter sentiment tweets will increase the stock value of a given company.
Two companies from different industry sectors will be analyzed in effect. They are car manufacturer BMW and technology giants Apple. Again, this study is to see whether the stock prices would correlate to the sentiment tweets as outlined earlier for these two companies. The reason for choosing these two particular names is the fact they are prominent brands in their sectors. They release products on almost a regular basis with customers anticipating the release of their product launches. They also regularly show their presence within the business and financial news and play a big part within their respective market places in which they operate. Thus, it would be no surprise to have twitter as a resource to post and tweet about their name out in the open. As a result, the aim of this study would to see the entire sentiments for these two brands and identify whether there is a correlation with their overall performance of stock value.
To help further define the main purpose outlined towards this dissertation, it is imperative to consider the implications that the use of twitter sentiments will have on the potential corresponding stock value on companies. Hence, this study will show a clear focus and consistency throughout the study outlining the intent of the study. Thus, it is important to remind the reader and in this research the following question:
ï¬ Does sentiment analysis on twitter correlates to stock value in a specific company?
Following on from this question, it is as vital then to point out in answering the research question, a hypothesis therefore must be conducted as follows. In this case, the sentiment analysis of public opinions towards a specific company is the dependent variable and the independent variable is the stock value of the company. This below outlines the following hypothesis:
ï¬ Hypotheses: The stock value of a specific company is correlated with sentiment analysis of tweets towards the company.
ï¬ H0: The stock value of a specific company is independent from sentiment analysis of tweets towards the company.
ï¬ H1: The stock value of a specific company is correlated to sentiment analysis of tweets towards the company.
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