Simple, short, and compact hashtags cover a wide range of information on social networks. Although many works in the field of natural language processing (NLP) have demonstrated the importance of hashtag recommendation, hashtag recommendation for images has barely been studied. In this paper, we introduce the HARRISON dataset, a benchmark on hashtag recommendation for real world images in socia...

In microblogging services, users can generate hashtags to categorize their tweets. However, a majority of microblogs do not contain hashtags, which has intrigued active research on the problem of automatic hashtag recommendation for microblogs. Previous work conducted on this problem mostly does not take the user’s preference into consideration. In this paper, we propose a novel personalized ha...

Hashtags have become a powerful tool in social platforms such as Twitter to categorize and search for content, and to spread short messages across members of the social network. In this paper, we study temporal hashtag usage practices in Twitter with the aim of designing a cognitive-inspired hashtag recommendation algorithm we call BLLI,S . Our main idea is to incorporate the effect of time on ...

The rise in popularity of microblogging services like Twitter has led to increased use of content annotation strategies like the hashtag. Hashtags provide users with a tagging mechanism to help organize, group, and create visibility for their posts. This is a simple idea but can be challenging for the user in practice which leads to infrequent usage. In this paper, we will investigate various m...

Background Twitter has evolved into a powerful communication and information sharing tool used by millions of people around the world to post what is happening now. A hashtag, a keyword prefixed with a hash symbol (#), is a feature in Twitter to organize tweets and facilitate effective search among a massive volume of data. In this paper, we propose an automatic hashtag recommendation system th...

Microblogging services allow users to create hashtags to categorize their posts. In recent years, the task of recommending hashtags for microblogs has been given increasing attention. However, most of existing methods depend on hand-crafted features. Motivated by the successful use of long short-term memory (LSTM) for many natural language processing tasks, in this paper, we adopt LSTM to learn...

Presence of spam tweets in a datasetmay affect the choices of feature selection, algorithm formulation, and system evaluation for many applications. However, most existing studies have not considered the impact of spam tweets. In this paper, we study the impact of spam tweets on hashtag recommendation for hyperlinked tweets (i.e., tweets containing URLs) in HSpam14 dataset. HSpam14 is a collect...

Along with the increasing requirements, the hashtag recommendation task for microblogs has been receiving considerable attention in recent years. Various researchers have studied the problem from different aspects. However, most of these methods usually need handcrafted features. Motivated by the successful use of convolutional neural networks (CNNs) for many natural language processing tasks, ...