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Asian Journal of Applied Science and Engineering
Article . 2020 . Peer-reviewed
License: CC BY NC
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Location Tracking via User Feed through Social Platforms to Detect Sentiments & Act on Those Analytical Data

Authors: Paruchuri, Harish;

Location Tracking via User Feed through Social Platforms to Detect Sentiments & Act on Those Analytical Data

Abstract

Tracking the reactions of users through social media to discover clients or audience sentiment and determining how best such analyzed data appears to offer owners of products, goods, and services online an opportunity to size up the performance of such content and acknowledge the general feeling. This article would adequately define what is meant by Social Media Sentiment Analysis. The core reasons why social media sentiment investigation is essential are adequately examined. The various areas where any content creator seeking to leverage social media feedback and opinions should channel its energy. It is also important to note that this article revealed how trackers could conduct a thorough result-based social media sentiment analysis and the available tools to operate it effectively. Most importantly, the potent methodologies through which a favorable sentiment can be generated towards any product, brand, content, or goods, and services whatsoever is sufficiently underpinned, and no doubt a determining utilization of these strategies will spur up patronage and ensure audience satisfaction due to the confidence achieved through genuine communication.

Related Organizations
Keywords

Social Media Content, GPS, Sentiments Analytics, Location Tracking

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citations
The total number of citations received by all articles of the researcher of interest.
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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