";s:4:"text";s:5370:" For evaluation we use manually curated violent events with rich features—such as actor, target, time, and location—as well as news articles data collected over the MENA region by Arabia Inform.It has been previously demonstrated that the bursty dynamics of terrorist activity can be well-captured by an appropriately designed Another important challenge for developing high-fidelity models for MANSA events is the availability of reliable, up-to-date historical data for generating real-time predictions. The GSR represents the occurrence of an event on a given day at a specific location by a specific actor. Finally, we present an evaluation of our models in Section 4 and discuss our findings in Section 5.There has been a significant interest in modeling the activities of terrorist groups.Developing a precise model for the dynamic behavior of time series is a challenging problem and an essential one for the success of forecasting methods. We use cookies to offer you a better experience, personalize content, tailor advertising, provide social media features, and better understand the use of our services.To learn more or modify/prevent the use of cookies, see our We use cookies to make interactions with our website easy and meaningful, to better understand the use of our services, and to tailor advertising. We transfer these event counts for each model to meaningful warnings with sampling each event detail field from its corresponding empirical distribution of the fields. Our results indicate that the signals extracted from streaming news sources can indeed lead to more accurate forecasts.The rest of the paper is organized as follows: Section 2 discusses relevant research on event forecasting and Section 3 presents models that we exploit for forecasting MANSA events. For the RARE model, we use topic-based temporal features as external signals (see Section 4.1). I am a computer science PhD student at the University of Southern California in the Computational Social Science Lab (CSSL). Hobbies include cooking and arting.Brendan is a PhD student in the Computer Science Department. Project Github. To see the efficacy of this approach, we generate warnings at the country level (Syria and Iraq) for two different types of events (military action and non-state actor events) over the months from March to September 2017. ARIMA stands for autoregressive integrated moving average (MA). Assad Oberai AME, USC Verified email at usc.edu. Brendan Kennedy. We extract post-...Research has shown that accounting for moral sentiment in natural language can yield insight into a variety of on- and off-line phenomena such as message diffusion, protest dynamics, and social distancing. Aida also works at the USC Institute of Armenian Studies. the site you are agreeing to our use of cookies. He also loves to travel and explore new places.Nikki is a second-year undergraduate student studying Cognitive Science. She is especially interested in the topics of mental health, addiction, and cognition. Our goals are to answer the following questions.Can the HMM capture latent structures in activities executed by various actors?How do the proposed models perform with MANSA events at actor, country, and city levels?Which external signals are good indicators for forecasting MANSA events?How can we generate warnings given predicted event counts? This constrains research interested in the study o...Computer-Aided Diagnosis (CAD) systems can provide a second opinion for either identifying suspicious regions on a medical image or predicting the degree of malignancy for a detected suspicious region. Next, we focus on the task of reconstructing the hidden trajectory of the actor. He is interested in studying the phenomena of belief change and persuasion in the context of the adoption of political ideologies, moral values, and scientific beliefs.