About
27
Publications
9,042
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308
Citations
Citations since 2017
Introduction
I currently work at the Institute of Informatics, University of Vienna, Vienna, Austria. My early research focused on the analysis of emotional messages during crisis events over social media, where I used the concept of emotion-exchange motifs to characterize structural patterns that emerge as people exchange specific emotions, including anger, fear, joy, surprise, and sadness. I am currently involved in investigating human coping strategies during crises.
Additional affiliations
March 2021 - present
November 2013 - March 2021
Education
March 2014 - November 2020
October 2009 - September 2011
Department of Informatics, University of Rijeka
Field of study
- Informatics
Publications
Publications (27)
In this paper, we provide a sentiment analysis of the Twitter discussion on the 2016 Austrian presidential elections. In particular, we extracted and analyzed a data-set consisting of 343645 Twitter messages related to the 2016 Austrian presidential elections. Our analysis combines methods from network science and sentiment analysis. Among other th...
Abstract In this paper, we present an analysis of the emotion-exchange patterns that arise from Twitter messages sent during emergency events. To this end, we performed a systematic structural analysis of the multiplex communication network that we derived from a data-set including more than 1.9 million tweets that have been sent during five recent...
We analyze a data-set including more than 4.5 million tweets related to four highly emotional riot events. In particular, we examine statistically significant structural patterns that emerge as humans directly engage in an exchange of emotional messages with other humans on Twitter. Furthermore, we compare typical human-to-human communication patte...
In this paper, we analyze more than 16 million tweets that have been sent from 6.1 million Twitter accounts and are related to nine natural disasters. As part of our analysis, we identify eight basic emotions conveyed in these tweets. We found that during natural disasters, social media messages at first predominantly express fear, while sadness an...
##### Download link (IEEE Dataport): http://dx.doi.org/10.21227/yajb-6y77 ######
This dataset is a directed network that represents a direct message exchange among Twitter users during eighteen crisis events. The dataset comprises 645,339 unique user IDs and 1,396,709 edges that are labeled with respect to Plutchik's basic emotions (anger, fear, s...
In this paper, we discuss how emotional messages sent during crisis events shape the communication patterns on Twitter. To this end, we analyzed a data-set consisting of 23.3 million tweets that have been sent during eighteen different crisis events in ten different countries. In particular, we use the novel concept of emotion-exchange motifs to un...
With currently about three billion users, Online Social Networks (OSNs) provide an important channel for people to express their opinion, seek information, and engage in discussions during events of public interest, such as disease outbreaks, natural disasters, or political elections. Human perception of such events does not only depend on the circ...
Social bots are software programs that automatically produce messages and interact with human users on social media platforms. In this paper, we provide an analysis of the emotion-exchange patterns that arise from bot- and human-generated Twitter messages. In particular, we analyzed 1.3 million Twitter accounts that generated 4.4 million tweets rel...
In this paper, we present a study on 5.6 million messages that have been sent via Twitter, Facebook, and YouTube. The messages in our data set are related to 24 systematically chosen real-world events. For each of the 5.6 million messages, we first extracted emotion scores based on the eight basic emotions according to Plutchik’s wheel of emotions....
In this paper, we present a study on the emotions conveyed in bot-generated Twitter messages as compared to emotions conveyed in human-generated messages. Social bots are software programs that automatically produce messages and interact with human users on social media platforms. In recent years, bots have become quite complex and may mimic the be...
In this paper, we present a study on the impact of emotions on information diffusion during a riot event. In particular, we analyze a data-set consisting of more than 750 thousand social media messages related to the 2017 G20 summit that have been extracted from Facebook, Twitter, and YouTube. Because of the controversies surrounding police operati...
In this paper, we present a study on 4.4 million Twitter messages related to 24 systematically chosen real-world events. For each of the 4.4 million tweets, we first extracted sentiment scores based on the eight basic emotions according to Plutchik's wheel of emotions. Subsequently, we investigated the effects of shifts in the emotional valence on...
In recent years, emotions expressed in social media messages have become a vivid research topic due to their influence on the spread of misinformation and online radicalization over online social networks. Thus, it is important to correctly identify emotions in order to make inferences from social media messages. In this paper, we report on the per...
In this paper, we provide a systematic analysis of the Twitter discussion on the 2016 Austrian presidential elections. In particular, we extracted and analyzed a data-set consisting of 343645 Twitter messages related to the 2016 Austrian presidential elections. Our analysis combines methods from network science, sentiment analysis, as well as bot d...
Purpose
Ever since Mark Weiser coined the term “ubiquitous computing” (ubicomp) in 1988, there has been a general interest in proposing various solutions that would support his vision. However, attacks targeting devices and services of a ubicomp environment have demonstrated not only different privacy issues, but also a risk of endangering user’s l...
![Fig. 1 The general model of the AAI. [1]](profile/Natasa-Hoic-Bozic/publication/257076435/figure/fig1/AS:297422136856588@1447922371857/The-general-model-of-the-AAI-1_Q320.jpg)
Advances in technology brought changes to many sectors, including education. With the development of mobile devices and availability of low cost or free online services and applications, the content-centric course design approach and the standard LMS are no longer meeting the student’s preferences and needs. The development of cloud computing and i...
Operations Research is a compulsory course taught in the winter semester at the Department of Informatics, University of Rijeka. The profile of students that are enrolled into this course varies. It includes single major Informartics students (a teacher training module, a module Information and Communication Systems and a module Business Informatic...
Learning management systems (LMS) have solved many issues with transferring traditionally taught courses to an online environment. Today, LMSs are an important part of universities world-wide, whether they are an addition to traditional classes or a platform for online courses. With the growing number of LMSs offered on the market, it is difficult...
This paper describes the e-learning model used in a course “Multimedia Systems,” given at the University of Rijeka, Croatia. The course was taught in a blended way, combining self-paced learning, f2f classroom learning, and online learning supported by the Moodle learning management system. The paper describes the technology for, and the methodolog...
Questions
Question (1)
Hi everyone. I am looking for some resources to detect anxiety in German texts (e.g. social media posts). Do you know of any annotated sets / lexica / tools that are available to researchers?
Any suggestions would be appreciated.
Projects
Project (1)
The goal of this project is to identify small, local, and statistically significant structures that are characteristic for an exchange of specific emotions on social media. We call such structures emotion-exchange motifs. The set of emotions we work with are Plutchik's eight basic emotions: anger, fear, disgust, sadness, joy, anticipation, trust, and surprise. Our case studies focus primarily on the direct messaging behavior during various types of crisis events (terror attacks, shootings, riots, and natural disasters). Our primary source of data is Twitter, though our studies also include YouTube and Facebook comments. As one of the aspects of our project, we also distinguish between human accounts and automated bot accounts to uncover the characteristic behavior for both types of users.
