Social bots can affect online communication among humans. We study this phenomenon by focusing on #YaMeCanse, the most active protest hashtag in the history of Twitter in Mexico. Accounts using the hashtag are classified using the BotOrNot bot detection tool. Our preliminary analysis suggests that bots played a critical role in disrupting online communication about the protest movement.

On microblogging services, people usually use hashtags to mark microblogs, which have a specific theme or content, making them easier for users to find. Hence, how to automatically recommend hashtags for microblogs has received much attention in recent years. Previous deep neural network-based hashtag recommendation approaches converted the task into a multiclass classification problem. However...

Twitter as a micro-blogging platform rose to instant fame mainly due to its minimalist features that allow seamless communication between users. As the conversations grew thick and faster, a placeholder feature called as Hashtags became important as it captured the themes behind the tweets. Prior studies have investigated the conversation dynamics, interplay with other media platforms and commu...

En esta edición, la revista #ashtag de Corporación Unificada Nacional Educación Superior (CUN) presenta reflexiones acerca las tecnologías cuarta revolución industrial y también sobre clásicas que permiten resolver problemas cotidianos configurar nuevos estándares vida personas. Esta publicación ve luz gracias al esfuerzo conjunto Unidad Publicaciones, Dirección Investigación el Programa Ingeni...

This paper explores humour recognition for Twitter-based hashtag games. Given their popularity, frequency, and relatively formulaic nature, these games make a good target for computational humour research and can leverage Twitter likes and retweets as humour judgments. In this work, we use pairwise relative humour judgments to examine several measures of semantic relatedness between setups and ...

Online information propagates differently on the web, some of which can be viral. In this paper, first we introduce a simple standard deviation sigma levels based Tweet volume breakout definition, then we proceed to determine patterns of re-tweet network measures to predict whether a hashtag volume will breakout or not. We also developed a visualization tool to help trace the evolution of hasht...

In this paper, we outline our experiments carried out at the TREC Microblog Track 2011. Our system is based on a plain text index extracted from Tweets crawled from twitter.com. This index has been used to retrieve candidate Tweets for the given topics. The resulting Tweets were post-processed and then analyzed using three different approaches: (i) a burst detection approach, (ii) a hashtag ana...

This paper examines the community formed by the Twitter users that used a city-level hashtag. In particular, we provide a network perspective of the city of Athens, Greece, as demonstrated by the analysis and visualization of the relevant Twitter hashtag data, in order to present both an overview and deeper insights at the microblogging practices of this geographic local network. Further analys...

1. Hashtags increasingly used to convey the actual message in tweets. Phrases and sentences turned into a hashtag. 2. Word with sentiment may trap inside a multi-word hashtag 3. Noisy and compact nature of language leads to hashtags very difficult to segment; sometimes depends on context. eg. #together; “to get her” or “together”? 4. Can we use carefully auto-segmented hashtags for training? RE...

Hashtag is definitely one of the most significant features of Twitter which now is spread all over the social networking services. It can serve different functions, and one of the most important is the designation of situation models. Using the method of Maximal Frequent Sequences we proved that the main idea of all data of one hashtag can be described in two or three phrases as a summary proce...