Related papers: Extracting and Analyzing Context Information in Us…
Context modeling and recognition represent complex tasks that allow mobile and ubiquitous computing applications to adapt to the user's situation. Current solutions mainly focus on limited context information generally processed on…
Our paper studies the predictability of online speech -- that is, how well language models learn to model the distribution of user generated content on X (previously Twitter). We define predictability as a measure of the model's…
We make decisions by reacting to changes in the real world, in particular, the emergence and disappearance of impermanent entities such as events, restaurants, and services. Because we want to avoid missing out on opportunities or making…
We receive several essential updates on our smartphones in the form of SMS, documents, voice messages, etc. that get buried beneath the clutter of content. We often do not realize the key information without going through the full content.…
Nowadays, people from all around the world use social media sites to share information. Twitter for example is a platform in which users send, read posts known as tweets and interact with different communities. Users share their daily…
In this paper, we describe our approaches to TREC Real-Time Summarization of Twitter. We focus on real time push notification scenario, which requires a system monitors the stream of sampled tweets and returns the tweets relevant and novel…
In this paper, we present TwiSent, a sentiment analysis system for Twitter. Based on the topic searched, TwiSent collects tweets pertaining to it and categorizes them into the different polarity classes positive, negative and objective.…
As the online world continues its exponential growth, interpersonal communication has come to play an increasingly central role in opinion formation and change. In order to help users better engage with each other online, we study a…
With the rapid advancement of large language models (LLMs), intelligent conversational assistants have demonstrated remarkable capabilities across various domains. However, they still mainly rely on explicit textual input and do not know…
Social networks play a fundamental role in propagation of information and news. Characterizing the content of the messages becomes vital for different tasks, like breaking news detection, personalized message recommendation, fake users…
We present a transformer-based sarcasm detection model that accounts for the context from the entire conversation thread for more robust predictions. Our model uses deep transformer layers to perform multi-head attentions among the target…
When a software bug is reported, developers engage in a discussion to collaboratively resolve it. While the solution is likely formulated within the discussion, it is often buried in a large amount of text, making it difficult to comprehend…
Social media platforms have become new battlegrounds for anti-social elements, with misinformation being the weapon of choice. Fact-checking organizations try to debunk as many claims as possible while staying true to their journalistic…
One of the primary mechanisms by which developers receive feedback about in-field failures of software from users is through bug reports. Unfortunately, the quality of manually written bug reports can vary widely due to the effort required…
In times of crisis, identifying the essential needs is a crucial step to providing appropriate resources and services to affected entities. Social media platforms such as Twitter contain vast amount of information about the general public's…
Social media users who report content are key allies in the management of online misinformation, however, no research has been conducted yet to understand their role and the different trends underlying their reporting activity. We suggest…
Documenting the context in which data are collected is an integral part of the scientific research lifecycle. In field-based research, contextual information provides a detailed description of scientific practices and thus enables data…
Existing dialog datasets contain a sequence of utterances and responses without any explicit background knowledge associated with them. This has resulted in the development of models which treat conversation as a sequence-to-sequence…
We show that information about social relationships can be used to improve user-level sentiment analysis. The main motivation behind our approach is that users that are somehow "connected" may be more likely to hold similar opinions;…
Software development is a complex endeavor that depends on a wide variety of contextual factors involving a large amount of distributed information. This knowledge could include: technology-related tasks, software operating environments and…