Decoding the New World Language: Analyzing the Popularity, Roles, and Utility of Emojis
Decoding the New World Language: Analyzing the Popularity, Roles, and Utility of Emojis
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解码新世界语言：分析表情符号的流行度、作用和实用性
DOI：
10.1145/3308560.3316541
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Mei, Qiaozhu
中科院分区：
文献类型：
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作者：
Mei, Qiaozhu
简体中文已迅速成为全球用户使用的通用语言，用于日常任务，跨越语言障碍，以及不同的应用程序和平台。表情符号的流行迅速引起了自然语言处理、Web挖掘、普适计算、人机交互等多个研究领域以及社会科学、艺术、心理学、语言学等学科的广泛关注。本演讲总结了我的研究小组和我们的合作者最近在分析大规模表情符号数据方面所做的努力。全球用户对表情符号的使用呈现出有趣的共性和差异。在我们对212个国家的数百万智能手机用户使用表情符号的分析中，我们发现表情符号的不同偏好和使用为理解互联网用户的文化差异提供了丰富的信号，这与霍夫施泰德的文化维度相关[4]。通过共同学习单词和表情符号的嵌入和拓扑结构，我们发现表情符号对单词既有互补关系，也有补充关系。基于表情符号在语义空间中的结构特性，我们能够解开表情符号流行背后的几个因素[1]。本演讲还强调了表情符号的实用性。一般来说，表情符号已被互联网用户用作文字补充，以描述对象和情况，表达情感，或表达幽默和讽刺;它们也被用作通信工具，以吸引注意力，调整语气或建立个人关系。使用表情符号的好处超出了这些意图。特别是，我们表明，在GitHub上的问题报告的描述中包含表情符号会导致更多的用户响应问题并更快地解决问题。AI系统还可以利用大规模的表情符号数据来提高Web挖掘服务的质量。特别是，智能机器学习系统可以根据用户在线使用表情符号的方式来推断潜在的主题，情感甚至人口统计信息。我们的分析揭示了表情符号的女性和男性用户之间存在相当大的差异，这足以让机器学习算法准确预测用户的性别。在为性别群体定制的Web服务中，基于表情符号构建的性别推断模型可以补充那些基于文本或行为痕迹的模型，具有更少的隐私问题[2]。表情符号还可以用作跨越语言障碍的Web挖掘任务的桥梁工具，特别是从具有丰富训练标签的语言（例如，英语）到高级自然语言处理任务难以实现的语言[3]。通过这座桥梁，人工智能系统和Web服务的开发者能够减少由于不同语言的人类注释不平衡而导致的国际用户所获得的服务质量的不平等。总体而言，表情符号已经从视觉表意符号演变为人工智能和新Web时代的全新世界语言。表情符号的受欢迎程度、作用和实用性都超出了人们的初衷，这为未来的研究创造了巨大的机会，需要多学科的共同努力。
Emojis have quickly become a universal language that is used by worldwide users, for everyday tasks, across language barriers, and in different apps and platforms. The prevalence of emojis has quickly attracted great attentions from various research communities such as natural language processing, Web mining, ubiquitous computing, and human-computer interaction, as well as other disciplines including social science, arts, psychology, and linguistics.This talk summarizes the recent efforts made by my research group and our collaborators on analyzing large-scale emoji data. The usage of emojis by worldwide users presents interesting commonality as well as divergence. In our analysis of emoji usage by millions of smartphone users in 212 countries, we show that the different preferences and usage of emojis provide rich signals for understanding the cultural differences of Internet users, which correlate with the Hofstede’s cultural dimensions [4].Emojis play different roles when used alongside text. Through jointly learning the embeddings and topological structures of words and emojis, we reveal that emojis present both complementary and supplementary relations to words. Based on the structural properties of emojis in the semantic spaces, we are able to untangle several factors behind the popularity of emojis [1].This talk also highlights the utility of emojis. In general, emojis have been used by Internet users as text supplements to describe objects and situations, express sentiments, or express humor and sarcasm; they are also used as communication tools to attract attention, adjust tones, or establish personal relationships. The benefit of using emojis goes beyond these intentions. In particular, we show that including emojis in the description of an issue report on GitHub results in the issue being responded to by more users and resolved sooner.Large-scale emoji data can also be utilized by AI systems to improve the quality of Web mining services. In particular, a smart machine learning system can infer the latent topics, sentiments, and even demographic information of users based on how they use emojis online. Our analysis reveals a considerable difference between female and male users of emojis, which is big enough for a machine learning algorithm to accurately predict the gender of a user. In Web services that are customized for gender groups, gender inference models built upon emojis can complement those based on text or behavioral traces with fewer privacy concerns [2].Emojis can be also used as an instrument to bridge Web mining tasks across language barriers, especially to transfer sentiment knowledge from a language with rich training labels (e.g., English) to languages that have been difficult for advanced natural language processing tasks [3]. Through this bridge, developers of AI systems and Web services are able to reduce the inequality in the quality of services received by the international users that has been caused by the imbalance of available human annotations in different languages.In general, emojis have evolved from visual ideograms to a brand-new world language in the era of AI and a new Web. The popularity, roles, and utility of emojis have all gone beyond people’s original intentions, which have created a huge opportunity for future research that calls for joint efforts from multiple disciplines.