In this paper we investigate the problem of recommending Twitter hashtags for users with known GPS location, learning online from the stream of geo-tagged tweets. Our method learns the relevance of regions in a geographical hierarchy, combined with the local popularity of the hashtag. Unlike in typical collaborative filtering settings, trends and geolocation turns out to be more important than ...

The task of recommending hashtags for microblogs has been received considerable attention in recent years, and many applications can reap enormous benefits from it. Various approaches have been proposed to study the problem from different aspects. However, the impacts of temporal and personal factors have rarely been considered in the existing methods. In this paper, we propose a novel method t...

In microblogging services, users usually use hashtags to mark keywords or topics. Along with the fast growing of social network, the task of automatically recommending hashtags has received considerable attention in recent years. Previous works focused only on the use of textual information. However, many microblog posts contain not only texts but also the corresponding images. These images can...

Microblogging services continue to grow in popularity, users publish massive instant messages every day through them. Many tweets are marked with hashtags, which usually represent groups or topics of tweets. Hashtags may provide valuable information for lots of applications, such as retrieval, opinion mining, classification, and so on. However, since hashtags should be manually annotated, only ...

Previous personalized hashtag recommendations have been able to recommend suitable hashtags for a given microblog. Despite their performance improvement, we argue that three challenges remain unexplored. First , prior studies capture user interests solely from user-hashtag interactions are dire...

Twitter network is currently overwhelmed by massive amount of tweets generated by its users. To effectively organize and search tweets, users have to depend on appropriate hashtags inserted into tweets. We begin our research on hashtags by first analyzing a Twitter dataset generated by more than 150,000 Singapore users over a three-month period. Among several interesting findings about hashtag ...

In social networking/microblogging environments, #tag is often used for categorizing messages and marking their key points. Also, since some social networks such as twitter apply restrictions on the number of characters in messages, #tags can serve as a useful tool for helping users express their messages. In this paper, a new knowledge-intensive content-based #tag recommendation system is intr...

How can micro-blogging activities on Twitter be leveraged for user modeling and personalization? In this paper we investigate this question and introduce a framework for user modeling on Twitter which enriches the semantics of Twitter messages (tweets) and identifies topics and entities (e.g. persons, events, products) mentioned in tweets. We analyze how strategies for constructing hashtag-base...

Twitter is a fast growing real-time social media tool. As Twitter evolves, more and more people are partaking in sharing what is happening around the world through various Twitter applications. Hashtag use has become a unique tagging convention to help associate Twitter messages with certain events or contexts. Prefixed by a # symbol with a keyword, a Twitter hashtag serves as a bottom-up userp...