Related papers: Exploiting Social Networks. Technological Trends (…
Information technology (IT) has been used widely in many aspects of our daily life. After discuss politics related aspects for some articles. In this article author would like to discuss social media for students learning environment.…
The global spread of misinformation and concerns about content trustworthiness have driven the development of automated fact-checking systems. Since false information often exploits social media dynamics such as "likes" and user networks to…
We present a new model of the evolutionary dynamics and the growth of on-line social networks. The model emulates people's strategies for acquiring information in social networks, emphasising the local subjective view of an individual and…
Recognizing named entities in a document is a key task in many NLP applications. Although current state-of-the-art approaches to this task reach a high performance on clean text (e.g. newswire genres), those algorithms dramatically degrade…
Social network based applications have experienced exponential growth in recent years. One of the reasons for this rise is that this application domain offers a particularly fertile place to test and develop the most advanced computational…
Recent network traffic classification methods benefitfrom machine learning (ML) technology. However, there aremany challenges due to use of ML, such as: lack of high-qualityannotated datasets, data-drifts and other effects causing aging…
Complaining is a speech act extensively used by humans to communicate a negative inconsistency between reality and expectations. Previous work on automatically identifying complaints in social media has focused on using feature-based and…
This paper presents models and algorithms for interactive sensing in social networks where individuals act as sensors and the information exchange between individuals is exploited to optimize sensing. Social learning is used to model the…
We introduce the problem of proficiency modeling: Given a user's posts on a social media platform, the task is to identify the subset of posts or topics for which the user has some level of proficiency. This enables the filtering and…
Named Entity Recognition for social media data is challenging because of its inherent noisiness. In addition to improper grammatical structures, it contains spelling inconsistencies and numerous informal abbreviations. We propose a novel…
A text network refers to a data type that each vertex is associated with a text document and the relationship between documents is represented by edges. The proliferation of text networks such as hyperlinked webpages and academic citation…
Social media is a great source of data for users reporting information and regarding their health and how various things have had an effect on them. This paper presents various approaches using Transformers and Large Language Models and…
Fake news detection has become a research area that goes way beyond a purely academic interest as it has direct implications on our society as a whole. Recent advances have primarily focused on textbased approaches. However, it has become…
Social Search research deals with studying methodologies exploiting social information to better satisfy user information needs in Online Social Media while simplifying the search effort and consequently reducing the time spent and the…
Social media platforms offer numerous benefits and allow people to come together for various causes. Many communities, academia, government agencies, institutions, healthcare, entertainment, and businesses are on social media platforms.…
Social networking and micro-blogging services, such as Twitter, play an important role in sharing digital information. Despite the popularity and usefulness of social media, they are regularly abused by corrupt users. One of these nefarious…
STEM (Science, Technology, Engineering, and Mathematics) fields have become increasingly central to U.S. economic competitiveness and growth. The shortage in the STEM workforce has brought promoting STEM education upfront. The rapid growth…
In many simulation studies involving networks there is the need to rely on a sample network to perform the simulation experiments. In many cases, real network data is not available due to privacy concerns. In that case we can recourse to…
In the last decade, social networks became most popular medium for communication and interaction. As an example, micro-blogging service Twitter has more than 200 million registered users who exchange more than 65 million posts per day.…
Two main approaches to using social network information in recommendation have emerged: augmenting collaborative filtering with social data and algorithms that use only ego-centric data. We compare the two approaches using movie and music…