Related papers: A Tutorial on Event Detection using Social Media D…

Social media is increasingly used by humans to express their feelings and opinions in the form of short text messages. Detecting sentiments in the text has a wide range of applications including identifying anxiety or depression of…

Social networks have become a part in the daily life of millions of users, which offer wide range of interests and practices. The main characteristic of social networks is its ability to gather different individuals around a common point of…

Social media data is inherently rich, as it includes not only text content, but also users, geolocation, entities, temporal information, and their relationships. This data richness can be effectively modeled using heterogeneous information…

Social media have become a valuable source for extracting data about societal crises and an important outlet to disseminate official information. Government agencies are increasingly turning to social media to use it as a mouthpiece in…

Despite the significant efforts made by the research community in recent years, automatically acquiring valuable information about high impact-events from social media remains challenging. We present EviDense, a graph-based approach for…

Social media data has been increasingly used to study biomedical and health-related phenomena. From cohort level discussions of a condition to planetary level analyses of sentiment, social media has provided scientists with unprecedented…

Social media can be used for disaster risk reduction as a complement to traditional information sources, and the literature has suggested numerous ways to achieve this. In the case of floods, for instance, data collection from social media…

Events are happening in real-world and real-time, which can be planned and organized for occasions, such as social gatherings, festival celebrations, influential meetings or sports activities. Social media platforms generate a lot of…

Publicly available data is increasing rapidly, and will continue to grow with the advancement of technologies in sensors, smartphones and the Internet of Things. Data from multiple sources can improve coverage and provide more relevant…

Large relational-event history data stemming from large networks are becoming increasingly available due to recent technological developments (e.g. digital communication, online databases, etc). This opens many new doors to learning about…

The increasing use of social networks generates enormous amounts of data that can be used for many types of analysis. Some of these data have temporal and geographical information, which can be used for comprehensive examination. In this…

Social media for news consumption is becoming increasingly popular due to its easy access, fast dissemination, and low cost. However, social media also enable the wide propagation of "fake news", i.e., news with intentionally false…

We present a new machine learning and text information extraction approach to detection of cyber threat events in Twitter that are novel (previously non-extant) and developing (marked by significance with respect to similarity with a…

This workshop paper reports on an ongoing mixed-methods study on the two arguably most popular social network sites, Facebook and Twitter, for the same users. The overarching goal of the study is to shed light into the nuances of social…

Social networks have been widely studied over the last century from multiple disciplines to understand societal issues such as inequality in employment rates, managerial performance, and epidemic spread. Today, these and many more issues…

With the proliferation of social media over the last decade, determining people's attitude with respect to a specific topic, document, interaction or events has fueled research interest in natural language processing and introduced a new…

Consuming news from social media is becoming increasingly popular. Social media appeals to users due to its fast dissemination of information, low cost, and easy access. However, social media also enables the widespread of fake news.…

Large-scale databases of human activity in social media have captured scientific and policy attention, producing a flood of research and discussion. This paper considers methodological and conceptual challenges for this emergent field, with…

In this paper, we introduce the new problem of extracting fine-grained traffic information from Twitter streams by also making publicly available the two (constructed) traffic-related datasets from Belgium and the Brussels capital region.…

With the recent emergence and the explosion of users in social networks, Internet users have come to know more about other people or companies through information obtained from online groups or communities and therefore meet new…