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.

TweetNLP 是一个支持社交媒体中自然语言处理任务（包括情感分析、实体识别、表情预测和辱骂识别）的综合平台，其采用基于 Transformer 的语言模型，专门用于处理社交媒体文本，提供 Python 库、在线演示和教程等多种支持。