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Our innovation can track the sentiments of social media comments and tweets and produce the comprehensive reports about its analytics.
About
We have concluded from our analytics report on "Who Is Winning the Brexit Wars on Twitter?". The highlights were, the Pro-Brexit campaign is gaining a foothold among the British audiences and is gaining massive support from people on Twitter when compared with the Anti-Brexit Stance. Pro-Brexit Stance is increasing on a monthly basis, and it suggests people are more inclined towards “Britain leaving Europe”. It seems leaders supporting Brexit are more articulate and engaged. The report explored Brexit related Twitter activity, which occurred between 1st May 2019 and 31st October 2019. Using Citispotter's proprietary API, we investigated the Pro and Anti-Brexit stance of 3,378,009 tweets. Our aim was to detect trends on each side of the Brexit debate over a six-month period. Data were collected from Twitter, pre-processed for stop-words and special characters such as 'The', 'on' '.', '@', '!' which have no significance in determining stance. This data was further depicted through visualizations. We also identified clusters of words that featured prominently as part of stance detection on both sides of the debate through a word cloud. It would appear that the pro-Brexit tweets are more forceful in tone and volume. If the silent “minority” want to be heard, they need to up their game. For detailed information please see our case studies. https://drive.google.com/drive/folders/1QLJh-cEeqG5n5_X-b5bzCThG_L7z2O6h
Key Benefits
Key benefits to get analytics about trending (negative) sentiment on social media and early detection of any viral movement against them and protect their brand image. 1) With our innovation, the company can crunch their social media tweets/posts to understand the public stance towards them positive and negative both. 2) Identify volume trends of for or against stance. 3) Examine stance trends over the period of time – were there any changes? 4) Identify associated Hashtags.
Applications
1) Protect brand image 2) Detection of negative sentiment 3) Early detection of negative news