@article{MAKHILLIJSC201611621365,
    title = {Visualization Model for Viral Marketing},
    journal = {International Journal of Soft Computing},
    volume = {11},
    number = {6},
    pages = {418-426},
    year = {2016},
    issn = {1816-9503},
    doi = {ijscomp.2016.418.426},
    url = {https://makhillpublications.co/view-article.php?issn=1816-9503&doi=ijscomp.2016.418.426},
    author = {T.,Ravinder,S.K.,V. and},
    keywords = {Social network,social network analysis,viral marketing,influence maximization,visualization},
    abstract = {With technology advancing by leaps and bounds over the past couple of decades, communication
has now become much more convenient. Social media is an effective means of acquiring, organizing and
articulating information. Given the large population of people on social media, an idea or information can easily
be spread among the users. Social network analysis deals with the analyzing network of structure and with the
propagation of information. This opens up opportunity for advertisers who can advertise using viral marketing.
Our system uses a novel method of spreading the awareness of a product or an idea in a social network. The
system adopts Principal Component Analysis (PCA) technique of determining the threshold value of a user
which will help us in obtaining an accurate seed set from an influence maximization algorithm which is a distinct
advantage of our system. In addition, the system also provides statistical data regarding the spread of influence
useful to the user in decision making process.}
    }