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Twitter Dataset for Arabic Sentiment Analysis Arabic tweets. Samples hand-labeled as positive or negative. 2000 Text Classification 2014 [53] [54] N. Abdulla Buzz in Social Media Dataset Data from Twitter and Tom's Hardware. This dataset focuses on specific buzz topics being discussed on those sites.
HuffPost Data Visualization, analysis, interactive maps and real-time graphics. Browse, copy and fork our open-source software.; Remix thousands of aggregated polling results.
Gnip, Inc. was a social media API aggregation company that was purchased by Twitter in 2014. Headquartered in Boulder, Colorado, it provided data from dozens of social media websites via a single API. Gnip was among the first social media API aggregation services. Gnip is known as an early influencer in building the real-time web. [1]
Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
Common Crawl is a nonprofit 501(c)(3) organization that crawls the web and freely provides its archives and datasets to the public. [1] [2] Common Crawl's web archive consists of petabytes of data collected since 2008. [3] It completes crawls approximately once a month. [4] Common Crawl was founded by Gil Elbaz. [5]
Qloo developed an enterprise-grade API to support Twitter’s needs. Twitter ended up pivoting to enable brands to use the social platform for customer service and support, but Qloo was able to sell access to its cultural intelligence via API to many other enterprise clients, marking the official transition from a B2C company to a B2B company. [12]
Media Bias/Fact Check (MBFC) is an American website founded in 2015 by Dave M. Van Zandt. [1] It considers four main categories and multiple subcategories in assessing the "political bias" and "factual reporting" of media outlets, [2] [3] relying on a self-described "combination of objective measures and subjective analysis".
LangChain was launched in October 2022 as an open source project by Harrison Chase, while working at machine learning startup Robust Intelligence. The project quickly garnered popularity, [3] with improvements from hundreds of contributors on GitHub, trending discussions on Twitter, lively activity on the project's Discord server, many YouTube tutorials, and meetups in San Francisco and London.