A5061810530- Misinformation and Its Impacts
- Complex Network Analysis Techniques
- Social Media and Politics
- Opinion Dynamics and Social Influence
- Digital Marketing and Social Media
- Sentiment Analysis and Opinion Mining
- Hate Speech and Cyberbullying Detection
- Ethics and Social Impacts of AI
- Topic Modeling
- Impact of Technology on Adolescents
- Psychology of Moral and Emotional Judgment
- Caching and Content Delivery
- Human Mobility and Location-Based Analysis
- Spam and Phishing Detection
- Mental Health via Writing
- Advanced Text Analysis Techniques
- Impact of Light on Environment and Health
- Peer-to-Peer Network Technologies
- Privacy-Preserving Technologies in Data
- Digital Mental Health Interventions
- Adversarial Robustness in Machine Learning
- Wikis in Education and Collaboration
- Vaccine Coverage and Hesitancy
- Mental Health Research Topics
- Internet Traffic Analysis and Secure E-voting
Korea Advanced Institute of Science and Technology
2016-2025
Institute for Basic Science
2019-2025
Max Planck Institute for Security and Privacy
2024-2025
Kootenay Association for Science & Technology
2019-2023
Institute of Physiology and Basic Medicine
2023
Max Planck Institute for Software Systems
2008-2021
Max Planck Society
2009-2021
Korea Basic Science Institute
2020
Sabancı Üniversitesi
2020
Korea Institute of Science & Technology Information
2013
Directed links in social media could represent anything from intimate friendships to common interests, or even a passion for breaking news celebrity gossip. Such directed determine the flow of information and hence indicate user's influence on others — concept that is crucial sociology viral marketing. In this paper, using large amount data collected Twitter, we present an in-depth comparison three measures influence: indegree, retweets, mentions. Based these measures, investigate dynamics...
User Generated Content (UGC) is re-shaping the way people watch video and TV, with millions of producers consumers. In particular, UGC sites are creating new viewing patterns social interactions, empowering users to be more creative, developing business opportunities. To better understand impact systems, we have analyzed YouTube, world's largest VoD system. Based on a large amount data collected, provide an in-depth study YouTube other similar systems. popularity life-cycle videos, intrinsic...
Online social networks have become extremely popular; numerous sites allow users to interact and share content using links. Users of these often establish hundreds even thousands links with other users. Recently, researchers suggested examining the activity network - a that is based on actual interaction between users, rather than mere friendship distinguish strong weak While initial studies led insights how an structurally different from itself, natural important aspect has been...
Understanding how users behave when they connect to social networking sites creates opportunities for better interface design, richer studies of interactions, and improved design content distribution systems. In this paper, we present a first kind analysis user workloads in online networks. Our study is based on detailed clickstream data, collected over 12-day period, summarizing HTTP sessions 37,024 who accessed four popular networks: Orkut, MySpace, Hi5, LinkedIn. The data were from...
The problem of identifying rumors is practical importance especially in online social networks, since information can diffuse more rapidly and widely than the offline counterpart. In this paper, we identify characteristics by examining following three aspects diffusion: temporal, structural, linguistic. For temporal characteristics, propose a new periodic time series model that considers daily external shock cycles, where demonstrates rumor likely have fluctuations over time. We also key...
Online social networking sites like MySpace, Facebook, and Flickr have become a popular way to share disseminate content. Their massive popularity has led viral marketing techniques that attempt spread content, products, ideas on these sites. However, there is little data publicly available propagation in the real world few studies characterized how information spreads over current online networks.
User generated content (UGC), now with millions of video producers and consumers, is reshaping the way people watch TV. In particular, UGC sites are creating new viewing patterns social interactions, empowering users to be more creative, generating business opportunities. Compared traditional video-on-demand (VoD) systems, services allow request videos from a potentially unlimited selection in an asynchronous fashion. To better understand impact services, we have analyzed world's largest VoD...
This study determines the major difference between rumors and non-rumors explores rumor classification performance levels over varying time windows—from first three days to nearly two months. A comprehensive set of user, structural, linguistic, temporal features was examined their relative strength compared from near-complete date Twitter. Our contribution is at providing deep insight into cumulative spreading patterns as well tracking precise changes in predictive powers across features....
Several messages express opinions about events, products, and services, political views or even their author's emotional state mood. Sentiment analysis has been used in several applications including of the repercussions events social networks, products simply to better understand aspects communication Online Social Networks (OSNs). There are multiple methods for measuring sentiments, lexical-based approaches supervised machine learning methods. Despite wide use popularity some methods, it...
Emoticons are a key aspect of text-based communication, and the equivalent nonverbal cues to medium online chat, forums, social media like Twitter. As emoticons become more widespread in computer mediated vocabulary different symbols with subtle emotional distinctions emerges especially across cultures. In this paper, we investigate semantic, cultural, aspects emoticon usage on Twitter show that not limited conveying specific emotion or used as jokes, but rather socio-cultural norms, whose...
We present a preliminary but groundbreaking study of the media landscape Twitter. use public data on whom follows who to uncover common behaviour in consumption, relationship between various classes media, and diversity content which social links may bring. Our analysis shows that there is non-negligible amount indirect exposure, either through friends follow particular sources, or via retweeted messages. show exposure expands political news users are exposed surprising extent, increasing...
One's state of mind will influence her perception the world and people within it. In this paper, we explore attitudes behaviors toward online social media based on whether one is depressed or not. We conducted semi-structured face-to-face interviews with 14 active Twitter users, half whom were other non-depressed. Our results highlight key differences between two groups in terms towards such systems. Non-depressed individuals perceived as an information consuming sharing tool, while it a...
The COVID-19 pandemic has been damaging to the lives of people all around world. Accompanied by is an infodemic, abundant and uncontrolled spreading potentially harmful misinformation. infodemic may severely change pandemic's course interfering with public health interventions such as wearing masks, social distancing, vaccination. In particular, impact on vaccination critical because it holds key reverting pre-pandemic normalcy. This paper presents findings from a global survey extent...
Artificial intelligence chatbot research has focused on technical advances in natural language processing and validating the effectiveness of human-machine conversations specific settings. However, real-world chat data remain proprietary unexplored despite their growing popularity, new analyses uses effects mitigating negative moods are urgently needed.In this study, we investigated whether how artificial chatbots facilitate expression user emotions, specifically sadness depression. We also...
For half a century, television has been dominant and pervasive mass media, driving many technological advances. Despite its widespread usage importance to emerging applications, the ingrained TV viewing habits are not completely understood. This was primarily due difficulty of instrumenting monitoring devices at individual homes large scale. The recent boom Internet (IPTV) enabled us monitor user behavior network an entire network. Such analysis can provide clearer picture how people watch...
Information propagation in online social networks like Twitter is unique that word-of-mouth and traditional media sources coexist. We collect a large amount of data from to compare the relative roles different types users play information flow. Using empirical on spread news about major international headlines as well minor topics, we investigate three spreaders: 1) mass BBC; 2) grassroots, consisting ordinary users; 3) evangelists, opinion leaders, politicians, celebrities, local...
Online social networking sites like MySpace and Flickr have become a popular way to share disseminate content. Their massive popularity has led the viral marketing of content, products, political campaigns on themselves. Despite excitement, precise mechanisms by which information is exchanged over these networks are not well understood.In this paper, we investigate cascades, or how disseminates through links in online networks. Using real traces 1,000 photos network collected from Flickr,...
Journal Article Cross-Cultural Comparison of Nonverbal Cues in Emoticons on Twitter: Evidence from Big Data Analysis Get access Jaram Park, Park 1Graduate School Culture Technology, Korea Advanced Institute Science and Daejeon, 305-701, Republic Search for other works by this author on: Oxford Academic Google Scholar Young Min Baek, Baek 2Department Communication, Yonsei University, Seoul, 120-749, Meeyoung Cha Volume 64, Issue 2, April 2014, Pages 333–354, https://doi.org/10.1111/jcom.12086...
While there is a large body of work examining the effects social network structure on innovation adoption, models to date have lacked considerations real geography or mass media. In this article, we show these features are crucial making more accurate predictions contagion and technology adoption at city-to-city scale. Using data from popular micro-blogging platform, Twitter, present model that places friendships in geographic space exposes individuals media influence. We homophily both...
Traditionally, users have discovered information on the Web by browsing or searching. Recently, word-of-mouth has emerged as a popular way of discovering Web, particularly social networking sites like Facebook and Twitter. On these sites, discover content following URLs posted their friends. Such based discovery become major driver traffic to many today. To better understand this phenomenon, in paper we present detailed analysis exchange among Twitter users. Among our key findings, show that...
Background: As online social media have become prominent, much effort has been spent on identifying users with depressive symptoms in order to aim at early diagnosis, treatment, and even prevention by using various media. In this paper, we focused Facebook discern any correlations between the platform's features users' symptoms. This work may be helpful trying reach detect large numbers of depressed individuals more easily. Objective: Our goal was develop a Web application identify...
The way in which social conventions emerge communities has been of interest to scientists for decades. Here we report on the emergence a particular convention Twitter—the indicate tweet is being reposted and attribute content its source. Initially, different variations were invented spread through Twitter network. inventors early adopters well-connected, active, core members community. diffusion networks these dense highly clustered, so no single user was critical adoption conventions....