Twitter messages often contain so-called hashtags to denote keywords related to them. Using a dataset of 29 million messages, I explore relations among these hashtags with respect to co-occurrences. Furthermore, I present an attempt to classify hashtags into five intuitive classes, using a machine-learning approach. The overall outcome is an interactive Web application to explore Twitter hash
Graduation date: 2016Social media sources such as Twitter represent a massively distributed social s...
ECML/PKDD PhD Track 2016 : European Conference on Machine Learning and Principles and Practice of Kn...
Background: Twitter has evolved into a powerful communication and information sharing tool used by m...
Hashtags, originally introduced in Twitter, are now becom-ing the most used way to tag short message...
Hashtags in Twitter posts may carry dif-ferent semantic payloads. Their dual form (word and label) m...
Abstract. Twitter enjoys enormous popularity as a micro-blogging ser-vice largely due to its simplic...
Includes bibliographical references (pages 47-50).Hashtags are a feature of tweets sometimes utilize...
With over 300 million active users, Twitter is among the largest online news and social networking s...
This dataset features all the tweetids and labels that were used to model the language of 24 hashtag...
This paper presents the TWEETDICT system prototype, which uses co-occurrence and frequency distribut...
Microblogging websites, such as Twitter, provide seemingly endless amount of textual information on ...
With over 300 million active users, Twitter is among the largest online news and social networking s...
This work constructs similarity network on raw Twitter data and uses LINE to learn embeddings on the...
Twitter is an important and influential social media platform, but much research into its uses remai...
Online social media such as Twitter, Facebook, Wikis and Linkedin have made a great impact on the wa...
Graduation date: 2016Social media sources such as Twitter represent a massively distributed social s...
ECML/PKDD PhD Track 2016 : European Conference on Machine Learning and Principles and Practice of Kn...
Background: Twitter has evolved into a powerful communication and information sharing tool used by m...
Hashtags, originally introduced in Twitter, are now becom-ing the most used way to tag short message...
Hashtags in Twitter posts may carry dif-ferent semantic payloads. Their dual form (word and label) m...
Abstract. Twitter enjoys enormous popularity as a micro-blogging ser-vice largely due to its simplic...
Includes bibliographical references (pages 47-50).Hashtags are a feature of tweets sometimes utilize...
With over 300 million active users, Twitter is among the largest online news and social networking s...
This dataset features all the tweetids and labels that were used to model the language of 24 hashtag...
This paper presents the TWEETDICT system prototype, which uses co-occurrence and frequency distribut...
Microblogging websites, such as Twitter, provide seemingly endless amount of textual information on ...
With over 300 million active users, Twitter is among the largest online news and social networking s...
This work constructs similarity network on raw Twitter data and uses LINE to learn embeddings on the...
Twitter is an important and influential social media platform, but much research into its uses remai...
Online social media such as Twitter, Facebook, Wikis and Linkedin have made a great impact on the wa...
Graduation date: 2016Social media sources such as Twitter represent a massively distributed social s...
ECML/PKDD PhD Track 2016 : European Conference on Machine Learning and Principles and Practice of Kn...
Background: Twitter has evolved into a powerful communication and information sharing tool used by m...