Streaming Big Data Analysis for Real-Time Sentiment based Targeted Advertising
| Autor: | Siddhant Deepak Shetty, Sujala D. Shetty, Lekha R. Nair |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Spark
General Computer Science Social network Computer science business.industry 020209 energy Sentiment analysis Big data Cloud computing 02 engineering and technology Public opinion Product (business) World Wide Web Cross-selling 0202 electrical engineering electronic engineering information engineering Targeted advertising Streaming big data processing 020201 artificial intelligence & image processing Relevance (information retrieval) Electrical and Electronic Engineering business Tweet sentiment analysis |
| Popis: | Big Data constituting from the information shared in the various social network sites have great relevance for research to be applied in diverse fields like marketing, politics, health or disaster management. Social network sites like Facebook and Twitter are now extensively used for conducting business, marketing products and services and collecting opinions and feedbacks regarding the same. Since data gathered from these sites regarding a product/brand are up-to-date and are mostly supplied voluntarily, it tends to be more realistic, massive and reflects the general public opinion. Its analysis on real time can lead to accurate insights and responding to the results sooner is undoubtedly advantageous than responding later. In this paper, a cloud based system for real time targeted advertising based on tweet sentiment analysis is designed and implemented using the big data processing engine Apache Spark, utilizing its streaming library. Application is meant to promote cross selling and provide better customer support. |
| Databáze: | OpenAIRE |
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