论文标题
TweetNLP：社交媒体的尖端自然语言处理
TweetNLP: Cutting-Edge Natural Language Processing for Social Media
论文作者
论文摘要
在本文中，我们介绍了TweetNLP，这是社交媒体中自然语言处理（NLP）的集成平台。 TweetNLP支持一套多种NLP任务，包括通用重点领域，例如情感分析和指定的实体识别，以及社交媒体特定的任务，例如表情符号预测和进攻性语言识别。特定于任务的系统由专门用于社交媒体文本的合理大小的基于变压器的语言模型（尤其是Twitter）提供动力，无需专门的硬件或云服务即可运行。 TweetNLP的主要贡献是：（1）使用适合社会领域的各种特定于任务的模型，用于支持社交媒体分析的现代工具包的集成Python库； （2）使用我们的模型进行无编码实验的交互式在线演示； （3）涵盖各种典型社交媒体应用的教程。
In this paper we present TweetNLP, an integrated platform for Natural Language Processing (NLP) in social media. TweetNLP supports a diverse set of NLP tasks, including generic focus areas such as sentiment analysis and named entity recognition, as well as social media-specific tasks such as emoji prediction and offensive language identification. Task-specific systems are powered by reasonably-sized Transformer-based language models specialized on social media text (in particular, Twitter) which can be run without the need for dedicated hardware or cloud services. The main contributions of TweetNLP are: (1) an integrated Python library for a modern toolkit supporting social media analysis using our various task-specific models adapted to the social domain; (2) an interactive online demo for codeless experimentation using our models; and (3) a tutorial covering a wide variety of typical social media applications.
