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Leveraging Social Media
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Leveraging Social Media

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Thoughts on how businesses can leverage social media to extract meaningful feedback and to generate superior recommendations and targeting.

Thoughts on how businesses can leverage social media to extract meaningful feedback and to generate superior recommendations and targeting.

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    Leveraging Social Media Leveraging Social Media Presentation Transcript

    • Leveraging social media Indrani Chakravarty © Indrani Chakravarty
    • Massive volumes of unstructured data • Social Networks: FaceBook, Twitter, LinkedIn, … • Online stores: amazon, wal-mart, e-bay, … • Blogs • Emails • SMS © Indrani Chakravarty
    • How can businesses benefit from Social Media • Leveraging Social Media for extracting meaningful feedback • Leveraging Social Media for better targeting © Indrani Chakravarty
    • Leveraging Social Media for extracting meaningful feedback Social Media opinions listen Analytics Platform Users Filter out noise, analyze/classify sentiments for each feature of the Sells Direct product & give a summary products feedback & recommendations to product/brand/sales management Marketing/Sales Actionable summary/ recommendations © Indrani Chakravarty
    • Underlying Technology -- an approach Linguistic pre-processing: 1)token normalization Collect adequate training 2) stop-words removal data(e.g. tweets) Tokenize 3) Stemming on a given topic. Hand-label the tweets 4) POS tagging tweets based on sentiment 5)N-gram analysis Apply learning algorithms to learn the model that fits the Compute TF-IDF weight relationship between Store tokens & for each token “i” the attribute set & the class-label corresponding in each tweet “j” in the training data posting lists in (example: SVM/ANN/ inverted index Bayesian/Nearest Neighbor) Test the model on fresh & unseen relevant tweets for sentiments. © Indrani Chakravarty
    • Leveraging Social Media for better targeting Targeting info Analytics platform Developers Advertisers 1. Cluster users based on: a) demographic & geo-information b) behavioral information, e.g. target • active/passive users ads • category of apps played most click • category of ads clicked most users play listen • type of products on which they apps give opinions most provide opinions interact/ 2. Offer recommendation/ share with Friends/ targeting (apps/ads) Network (social graph) Social Media © Indrani Chakravarty