نتایج جستجو برای: hashtag recommendation

تعداد نتایج: 34747  

2014
Florian Kunneman Christine Liebrecht Antal van den Bosch

Hashtags in Twitter posts may carry different semantic payloads. Their dual form (word and label) may serve to categorize the tweet, but may also add content to the message, or strengthen it. Some hashtags are related to emotions. In a study on emotional hashtags in Dutch Twitter posts we employ machine learning classifiers to test to what extent tweets that are stripped from their hashtag coul...

2012
Luca Rossi Matteo Magnani

The public by default nature of Twitter messages, together with the adoption of the #hashtag convention led, in few years, to the creation of a digital space able to host worldwide conversation on almost every kind of topic. From major TV shows to Natural disasters there is no contemporary event that does not have its own #hashtag to gather together the ongoing Twitter conversation. These topic...

Journal: :Eng. Appl. of AI 2016
Gerasimos Razis Ioannis Anagnostopoulos

On daily basis, millions of Twitter accounts post a vast number of tweets including numerous Twitter entities (mentions, replies, hashtags, photos, URLs). Many of these entities are used in common by many accounts. The more common entities are found in the messages of two different accounts, the more similar, in terms of content or interest, they tend to be. Towards this direction, we introduce...

Journal: :CoRR 2017
Andreas Veit Maximilian Nickel Serge J. Belongie Laurens van der Maaten

The variety, abundance, and structured nature of hashtags make them an interesting data source for training vision models. For instance, hashtags have the potential to significantly reduce the problem of manual supervision and annotation when learning vision models for a large number of concepts. However, a key challenge when learning from hashtags is that they are inherently subjective because...

Journal: :International Journal of Advanced Computer Science and Applications 2018

Journal: :International Journal of Sports Physiology and Performance 2017

2015
Credell Simeon Robert J. Hilderman

This paper seeks to identify sentiment and non-sentiment bearing hashtags by combining existing lexical resources. By using a lexicon-based approach, we achieve 86.3% and 94.5% precision in identifying sentiment and non-sentiment hashtags, respectively. Moreover, results obtained from both of our classification models demonstrate that using combined lexical, emotion and word resources is more e...

2015
Guillaume Tisserant Mathieu Roche Violaine Prince

Les hashtags sont des mots-clés que les utilisateurs de réseaux sociaux choisissent de mettre en avant dans leurs messages. Ils ont été popularisés sur le réseau social Twitter, qui a permis à ses utilisateurs de sélectionner des HashTags à suivre et d’afficher l’ensemble des messages contenant un HashTag suivi. Ils sont aujourd’hui utilisés sur les principaux réseaux sociaux, tels que Facebook...

2017
E Megan Lachmar Andrea K Wittenborn Katherine W Bogen Heather L McCauley

BACKGROUND Social media provides a context for billions of users to connect, express sentiments, and provide in-the-moment status updates. Because Twitter users tend to tweet emotional updates from daily life, the platform provides unique insights into experiences of mental health problems. Depression is not only one of the most prevalent health conditions but also carries a social stigma. Yet,...

Journal: :CoRR 2016
Ryan J. Gallagher Andrew J. Reagan Christopher M. Danforth Peter Sheridan Dodds

Since the shooting of Black teenager Michael Brown by White police officer Darren Wilson in Ferguson, Missouri, the protest hashtag #BlackLivesMatter has amplified critiques of extrajudicial killings of Black Americans. In response to #BlackLivesMatter, other Twitter users have adopted #AllLivesMatter, a counter-protest hashtag whose content argues that equal attention should be given to all li...

نمودار تعداد نتایج جستجو در هر سال

با کلیک روی نمودار نتایج را به سال انتشار فیلتر کنید