Built Data Aggregation Pipeline for Social Media Influencers |Python
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Overview

Social media influencers are a new breed of celebrities who wield enormous influence amongst their followers. There is a need to rank these influencers to help companies find great brand ambassadors for their products.

Solution Overview

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Built a data aggregation pipeline to extract tweets of social media influencers who have agreed to be scored by the Social IQ platform.

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These tweets are then pre-processed, re-tweets are contextualised ready to be ranked.

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Built a semantic indexing model using Universal Sentence Encoder (USE) to classify the tweets among 13 dimensions of social intelligence

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The preprocessed tweets are ranked based on the semantic indexer model and scored. Aggregate scores of the tweets are assigned to the authors.

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Built a robust dashboard to review the scores and Social IQ of the social media influencers across the Social IQ dimensions.

Impact

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Built an automated pipeline to continuously aggregate, score and rank the tweets of the authors.

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The live dashboard is accessible to the customers to review and make an informed judgment in selecting and assessing their brand ambassadors.

Technology

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