Feature extraction and event/trend detection in social media messages

人们越来越多地使用社交媒体（推特、博客和其他形式的公开帖子）来表达他们的意见和关切。许多公司现在有兴趣知道他们的品牌在网络空间中产生了什么样的聊天。 为此，In the Chat开发了挖掘工具，以检索和分类与特定公司的产品和服务有关的客户帖子。 拟议的研究将有助于In the Chat改进其社交媒体挖掘工具。 更具体地说，我们将开发新的算法来自动从短信中提取特征，以便于对短信进行分类，并开发新的技术来检测可能反映公众意见变化的事件或趋势。 这项工作将帮助In the Chat保持其在聊天挖掘方面的领导地位，并帮助加拿大和国际零售公司根据从社交媒体挖掘的公众反馈改善其客户服务。

People are increasingly using social media (tweets, blogs and other forms of public posts) to express their opinions and concerns. Many companies are now interested in knowing what kind of chatter their brand is generating in the cyber space. To that effect, In the Chat has developed mining tools to retrieve and classify customer posts related to the products and services of specific companies. The proposed research will help In the Chat to improve its social media mining tools. More specifically we will develop new algorithms to automatically extract features from text messages that can facilitate their classification as well as new techniques to detect events or trends that may reflect changes in the public's opinion. This work will help In the Chat to maintain its leadership position in chat mining as well as Canadian and international retail companies to improve their customer service based on public feedback mined from social media.