@article{MAKHILLJEAS201712914407,
    title = {Microblog Sentiment Analysis for Celebrity Endorsed Products},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {12},
    number = {9},
    pages = {2270-2274},
    year = {2017},
    issn = {1816-949x},
    doi = {jeasci.2017.2270.2274},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2017.2270.2274},
    author = {Jong,John and},
    keywords = {Start marketing,celebrity endorsed products,sentiment analysis,sentiment lexicon,NBA basketball},
    abstract = {Celebrity endorsed products such as NBA basketball star player endorsed shoes are typical examples
of star marketing. For the purpose of star marketing, companies need to monitor customer’s emotion and
sentiment to celebrities through social media such as Twitter, Instagram and Facebook. One step forward, in
this study, we aim to predict sales of celebrity endorsed products using sentiment analysis on social media data
on celebrities. Major fan group of celebrities are usually young generation and they use social media popularly
and frequently to share their emotion on celebrities. To apply sentiment analysis on the context we propose
a sentiment lexicon modification method based on supervised learning approach. Based on manually evaluated
social media contents on celebrities we identify domain-specific terms and their polarities which can contribute
to improve sentiment analysis performance. Using tweets on 10 NBA basketball star players and their endorsed
shoes sales data we perform experiments to show the usefulness of the proposed approach.}
    }