When Do Users Change Their Profile Information on Twitter?

We can see profile information such as name, description and location in order to know the user on social media. However, this profile information is not always fixed. If there is a change in the user's life, the profile information will be changed. In this study, we focus on user's profile information changes and analyze the timing and reasons for these changes on Twitter. The results indicate that the peak of profile information change occurs in April among Japanese users, but there was no such trend observed for English users throughout the year. Our analysis also shows that English users most frequently change their names on their birthdays, while Japanese users change their names as their Twitter engagement and activities decrease over time.Comment: IEEE BigData 2017 Workshop : The 2nd International Workshop on Application of Big Data for Computational Social Science (accepted

A Hybrid Convolutional Variational Autoencoder for Text Generation

In this paper we explore the effect of architectural choices on learning a Variational Autoencoder (VAE) for text generation. In contrast to the previously introduced VAE model for text where both the encoder and decoder are RNNs, we propose a novel hybrid architecture that blends fully feed-forward convolutional and deconvolutional components with a recurrent language model. Our architecture exhibits several attractive properties such as faster run time and convergence, ability to better handle long sequences and, more importantly, it helps to avoid some of the major difficulties posed by training VAE models on textual data

Fortnight

Fortnight is a two-week long, fully immersive, experience based in the interactions and communications of daily life. Up to 200 participants sign up to receive messages that are sent to their mobile phones, email, and home address; these messages contain a series of poetic nudges that encourage those participating to question their sense of place. Participants also receive daily invitations to visit locations throughout their city where they can pause to reflect on what it means to be here now. Fortnight enables the experience of “theatre” to penetrate beneath a seemingly brittle aesthetic surface of performance, deep into the consciousnesses of our participants as they begin to interact with and perceive world around us as the performance itself; the place where we act out our own daily lives. In Fortnight, the spectator becomes participant; the journey becomes narrative. Fortnight therefore subverts the notion of an audience, in which each spectator’s perspective is forced to examine not the situation and setting of performers on a stage, but rather the situation and setting of our own sense of place and the meaning we apportion to our everyday lives. Fortnight uses various forms of ubiquitous technology such as: Radio Frequency Identification (aka, RFID tags of the type contained in key fobs), which are used in badges sent to each participant that allow them to interact with real-world “portals” to trigger certain effects in their surroundings; QR technology (in the form of barcodes on posters that reveal additional hidden messages, should the participant choose to delve further; SMS messages; email; and, Twitter. Alongside this, older modes of communication such as handwritten letters, give Fortnight a decidedly low-fi aesthetic. Throughout Fortnight, participants are encouraged to explore the creative possibilities of pervasive and communicative media without reverting to mere technological fetishism. In Fortnight, each mode of communication is used not only for its functionality but also as symbols that bind the project and the participant together, rooting them to the here and now with the everyday tools of modern society. The mediated messages within Fortnight lead participants down a living, breathing rabbit hole where the familiar becomes unfamiliar and reality distorts. The project becomes an experience for the participant that is as immersive as their own life; creating an alternative reality, that not only co-exists alongside their own everyday realities, but also merges with them.This is a performance with shared responsibilities, reflecting the actions and consequences of our daily lives: what we put in, we get out

Real-Time Classification of Twitter Trends

Social media users give rise to social trends as they share about common interests, which can be triggered by different reasons. In this work, we explore the types of triggers that spark trends on Twitter, introducing a typology with following four types: 'news', 'ongoing events', 'memes', and 'commemoratives'. While previous research has analyzed trending topics in a long term, we look at the earliest tweets that produce a trend, with the aim of categorizing trends early on. This would allow to provide a filtered subset of trends to end users. We analyze and experiment with a set of straightforward language-independent features based on the social spread of trends to categorize them into the introduced typology. Our method provides an efficient way to accurately categorize trending topics without need of external data, enabling news organizations to discover breaking news in real-time, or to quickly identify viral memes that might enrich marketing decisions, among others. The analysis of social features also reveals patterns associated with each type of trend, such as tweets about ongoing events being shorter as many were likely sent from mobile devices, or memes having more retweets originating from a few trend-setters.Comment: Pre-print of article accepted for publication in Journal of the American Society for Information Science and Technology copyright @ 2013 (American Society for Information Science and Technology