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Connects users with communities for any topic that they are interested in, directly linking to and highlighting small to large creators for a truly diverse search result.
liondecorvn
Tagify: adding context to your content.
Ever been on social media and encountered hate speech or abusive language? Tweet Safely helps users' mental health by classifying accounts as safe to follow or using offensive and hateful language.
Web3fy your precious twitter bookmarks; visualize and filter using smart tags instantly.
Improve your customer relations! Find out what exactly is trending amongst social media platforms and your customers. An all-in-one interactive platform where companies have access to user sentiment.
We created a higher or lower game with tweets and sports rivalries
Natural Language Processor to predict the effect of fake verified accounts impersonating corporations and the effect of that on their stocks.
Analyze the amount of recent positive and negative tweets about the current gubernatorial candidates. This was done by training a model on sample tweets and analyzing tweets pulled by the Twitter API.
Gauging the mood of people in a given area based on conversations they are having
Know who you follow
kloes is a Twitter analytics application that gives you rich insights about any public Twitter profile. We analyze data about topics, mentions, hashtags, followers, location and hate speech's!
Because this couldn't go wrong. We haven't seen time and time again why you don't do this.
WarnMe notifications are available through an Android app! Avoid the area smarter.
Wondering which company will give you the most return for your investment? Introducing StockTalk! Leveraging co:here NLP models and the Twitter API, we can advise you on your next investment!
An NLP-based project that detects the instance of a tweet that contains a specific location and decides whether or not there is a hurricane there at the given time.
compare anything, whatever you want. Stocks, celebrities, animals ...
View galleries of retro-themed pictures based on user-selected Twitter hashtags.
The pandemic revealed the public messaging system was lacking as it was unable to produce timely, and cohesive messaging for specific communities. We looked into how this system can be improved.
A simple way to find what Twitter users think about any chosen topic.
Text and sentiment analysis of Tweet data about gender issues, done in python using Twitter API.
Using a Harvard dataset of climate-related tweets from 2017-2019, we analyzed the impact of these tweets on climate legislation.
Help scanner provides a platform that will help organizations who are willing to provide support in case of need for e.g. Donations, Distribution of groceries, cloths and charity work etc.
To tackle the spread of fake news, Team Payback presents Delphi, a SOTA User-preference aware GNN that harnesses the power of propagation graphs on Twitter to predict the veracity of a web article.
