Explainability in the field of event detection is a new emerging research area. For practitioners and users alike, explainability is essential to ensuring that models are widely adopted and trusted. Several research efforts have focused... more
The article is devoted to the topic of event detection based on the analysis of data related to space and time. The role of using neural networks in processing digital data that can be obtained from mobile communications companies is... more
News portals, such as Yahoo News or Google News, collect large amounts of documents from a variety of sources on a daily basis. Only a small portion of these documents can be selected and displayed on the homepage. Thus, there is a strong... more
Despite the importance of understanding causality, corpora addressing causal relations are limited. There is a discrepancy between existing annotation guidelines of event causality and conventional causality corpora that focus more on... more
Large scale social events that involve violence may have dramatic political, economic and social consequences. These events may result in higher crime rates, spreading of infectious diseases, economic crises, and even in migration... more
We detect and arrange events in private photo archives by putting these photos into context. The problem is seen as a fully automated mining in one's personal life and behavior. To this end, we build a contextual meaningful hierarchy of... more
Sorting one's own private photo collection is a time consuming and tedious task. We demonstrate our event-centered approach to perform this task fully automatically. In the course of the demonstration, we either use our own photo... more
Twitter Sentiment Analysis is the task of detecting opinions and sentiments in tweets using different algorithms. In our research work, we conducted a study to analyze and compare different Algorithms of Machine Learning (MLAs) for the... more
Social media data streams are an invaluable source for timely and up-to-date information about current events. As a consequence, several event detection techniques have been proposed in the literature in order to tap this information... more
The continuous growth of social networks and the active use of social media services result in massive amounts of user generated data. Our goal is to leverage social media users as "social sensors" in order to increase the situational... more
Building upon state-of-the-art algorithms for pedestrian detection and multi-object tracking, and inspired by sociological models of human collective behavior, we automatically detect small groups of individuals who are traveling... more
The Event Causality Identification Shared Task of CASE 2022 involved two subtasks working on the Causal News Corpus. Subtask 1 required participants to predict if a sentence contains a causal relation or not. This is a supervised binary... more
Internet users are getting more and more dependent for information regarding their daily lives. Most of the users are connected to each other using social networks. Social networking sites not only helps the users to connect and talk to... more
Nowadays, online social network "Twitter" represents a huge source of unrefined information in various formats (text, video, photo), especially during events and abnormal cases/incidents. New features for Twitter mobile application are... more
The popularity of online social networks (OSNs) is growing rapidly over time. People share their experiences with their friends and relatives with the help of multimedia such as image, video, text, etc. The amount of such shared... more
Despite the importance of understanding causality, corpora addressing causal relations are limited. There is a discrepancy between existing annotation guidelines of event causality and conventional causality corpora that focus more on... more
Despite the importance of understanding causality, corpora addressing causal relations are limited. There is a discrepancy between existing annotation guidelines of event causality and conventional causality corpora that focus more on... more
Zusammenfassung In Anknüpfung an den Vorschlag N. Luhmanns, die „Zeit“ dadurch an zentraler Stelle in die soziologische Theorie einzubauen, daß man das traditionelle Subjekt/Handlungs-Schema durch das Zeit/Handlungs-Schema ersetzt, soll... more
Information about events happening in the real world are generated online on social media in real-time. There is substantial research done to detect these events using information posted on websites like Twitter, Tumblr, and Instagram.... more
As the social media has gained more attention from users on the Internet, social media has been one of the most important information sources in the world. And, with the increasing popularity of social media, data which is posted on... more
Information about events happening in the real world are generated online on social media in real-time. There is substantial research done to detect these events using information posted on websites like Twitter, Tumblr, and Instagram.... more
In this demonstration, we introduce MLJ (MultiLingual Journalism, http://mljournalism.com), a first Web-based system that enables users to search any topic of latest tweets posted by media outlets and journalists beyond languages.... more
This article describes an original strategy for enhancing current state-of-the-art trackers through the use of motion priors, built as data-driven probabilistic motion models for moving targets. Our priors have a simple form and can... more
This paper presents the participation of the IRIT laboratory (University of Toulouse) to the Microblog Track of TREC 2015. This track consists in a real-time filtering task aiming at monitoring a stream of social media posts in accordance... more
Despite the importance of understanding causality, corpora addressing causal relations are limited. There is a discrepancy between existing annotation guidelines of event causality and conventional causality corpora that focus more on... more
Current language models are usually trained using a self-supervised scheme, where the main focus is learning representations at the word or sentence level. However, there has been limited progress in generating useful discourse-level... more
We introduce ReDites, a system for realtime event detection, tracking, monitoring and visualisation. It is designed to assist Information Analysts in understanding and exploring complex events as they unfold in the world. Events are... more
Twitter is now one of the main means for spread of ideas and information throughout the Web. Tweets discuss different trends, ideas, events, and so on. This gave rise to an increasing interest in analyzing tweets by the data mining... more
Analysis of public behavior plays an important role in crisis management, disaster response, and evacuation planning. Unfortunately, collecting relevant data can be costly and finding meaningful information for analysis is challenging. A... more
Understanding pedestrian dynamics in crowded scenes is an important problem. Given highly fragmented trajectories as input, we present a novel, fully unsupervised approach to automatically infer the semantic regions in a scene. Once the... more
Twitter, used in 200 countries with over 250 milliontweets a day, is a rich source of local news from aroundthe world. Many events of local importance are first reportedon Twitter, including many that never reach newschannels. Further,... more
From last few decades there is wide spread usage of social network platforms such as twitter or other micro blogging systems which contains huge amount of timely generated data. Tweeter is fastest means of information sharing where user... more
This paper develops a methodology to aggregate signals in a network regarding some hidden state of the world. We argue that focusing on edges around hubs will under certain circumstances amplify the faint signals disseminating in a... more
Social media websites can be used as a data source for mining public opinion on a variety of subjects including climate change. Twitter, in particular, allows for the evaluation of public opinion across both time and space because... more
Large scale social events that involve violence may have dramatic political, economic and social consequences. These events may result in higher crime rates, spreading of infectious diseases, economic crises, and even in migration... more
Many text classification problems in social networks, and other contexts, are also dynamic problems, where concepts drift through time, and meaningful labels are dynamic. In Twitter-based applications in particular, ensembles are often... more
This paper advances video analytics with a focus on crowd analysis for Hajj and Umrah pilgrimages. In recent years, there has been an increased interest in the advancement of video analytics and visible surveillance to improve the safety... more
In Wireless Sensor Networks (WSN) when an event is detected there is an increase in data traffic that might lead to packets being transmitted through the network close to the packet handling capacity of the WSN. The WSN experiences a... more
Congestion control is an extremely important area within wireless sensor networks (WSN), where traffic becomes greater than the aggregated or individual capacity of the underlying channels. Therefore, special considerations are required... more
Twitter's increasing popularity as a source of up to date news and information about current events has spawned a body of research on event detection techniques for social media data streams. Although all proposed approaches provide some... more
Twitter's increasing popularity as a source of up to date news and information about current events has spawned a body of research on event detection techniques for social media data streams. Although all proposed approaches provide some... more
With the advent of social media data, and in the pursuit of understanding meaning behind those data, text classification continues to grow in importance. Domain expertise is often needed to classify text effectively, but it is unlikely to... more
The main contribution of this paper is a compact representation of the 'short tracks' or tracklets present in a time window of a given video input, which allows to analyse and detect different crowd events. To proceed, first, tracklets... more
Despite the importance of understanding causality, corpora addressing causal relations are limited. There is a discrepancy between existing annotation guidelines of event causality and conventional causality corpora that focus more on... more