The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Nowadays blogging has become one of the most common and frequently employed methods for creating communities around specific topics of interest. This phenomenon is due to the existence of numerous online platforms that enable the creation with ease of blogs even for non-technical users. However, finding relevant blogs is a difficult and time-consuming process. This paper focuses on predicting whether...
This paper presents a research on using Word2Vec for determining implicit links in multi-participant Computer-Supported Collaborative Learning chat conversations. Word2Vec is a powerful and one of the newest Natural Language Processing semantic models used for computing text cohesion and similarity between documents. This research considers cohesion scores in terms of the strength of the semantic...
This study is aimed at presenting a new ReaderBench-based tool built to support candidates in increasing the quality of their CV for a job opening. Both the visual quality and the textual content are considered while also providing an overview and corresponding feedback for the entire CV. The presented CV analysis tool uses advanced Natural Language Processing techniques to interpret and understand...
Whether interested in personal work, in learning about trending topics, or in finding the structure of a specific domain, individuals' work of staying up-to-date has become more and more difficult due to the increasing information overflow. In our previous work our focus has been to create a semantic annotation model accompanied by dedicated views to explore the semantic similarities between scientific...
This paper presents a diachronic analysis centered on the exploration of differences between the writing styles of journalistic texts in Romanian language. This analysis is focused on the time evolution of this language across two adjacent regions, Bessarabia and Romania in two major periods that were marked by important historical differences. Our aim is to examine these language differences based...
Up to date, linguistic rhythm has been studied for speech, but the rhythm of written texts has been merely recognized, and not analyzed or interpreted in connection to natural language tasks. We provide an extension of the textual rhythmic features we proposed in previous work, and demonstrate its benefits for the task of text categorization. Rhythmic features require that the text be segmented in...
A new method to perform a bottom-up extraction and benchmark of the perceived multilevel smartness of complex ecosystems has been recently described and applied to territories and learning ecosystems like university campuses and schools. In this paper we study the resilience of our method by comparing and integrating the data collected in several European Campuses during two different academic years,...
The rise of social networks powered by the emergence of Web 2.0 unleashed a massive amount of generated user content. Concurrently with technology enhancements that facilitated its widespread, Web 2.0 became the engine which hastened the appearance of worldwide mass communication techniques. Alongside its advent, textual analysis changed as new user-centered content failed to comply with traditional...
Opinion mining and sentiment analysis are a trending research domain in Natural Language Processing focused on automatically extracting subjective information, feelings, opinions, ideas or emotions from texts. Our study is centered on identifying sentiments and opinions, as well as other latent linguistic dimensions expressed in on-line game reviews. Over 9500 entertainment game reviews from Amazon...
Social media tools are increasingly popular in Computer Supported Collaborative Learning and the analysis of students' contributions on these tools is an emerging research direction. Previous studies have mainly focused on examining quantitative behavior indicators on social media tools. In contrast, the approach proposed in this paper relies on the actual content analysis of each student's contributions...
Seeker is a serious game developed using the Unity game engine that focuses on a learning outcome: improving users' cognitive abilities. The user is confronted with a series of puzzles, has complete liberty in terms of traveling between game scenes and must adequately manage the available resources in order to solve the game. Cognitive abilities are challenged for resource management and decision...
Profiling online knowledge communities and determining their corresponding degree of newcomer integration based on existing members' involvement, posts and comments helps us better understand what drives the social trend and how knowledge is built nowadays. In this study we differentiate participation from collaboration, thus showing how opinion leaders emerge in a community. Therefore, while analyzing...
Each domain, along with its knowledge base, changes over time and every timeframe is centered on specific topics that emerge from different ongoing research projects. As searching for relevant resources is a time-consuming process, the automatic extraction of the most important and relevant articles from a domain becomes essential in supporting researchers in their day-to-day activities. The proposed...
Online knowledge building communities (oKBCs) are groups of people that interact, exchange opinions or share expertise in online environments. Profiling an oKBC addresses two main components: members and discussion threads. Their analysis reveals community's degree of integrativity defined as its capability of assimilating new members who subsequently approach an increasing number of further discussion...
Research efforts in terms of automatic textual complexity analysis are mainly focused on English vocabulary and few adaptations exist for other languages. Starting from a solid base in terms of discourse analysis and existing textual complexity assessment model for English, we introduce a French model trained on 200 documents extracted from school manuals pre-classified into five complexity classes...
Automatic evaluation is an efficient alternative of capturing the sentiments and the attitude of a targeted audience towards a specific topic or subject. The starting context of our research is represented by the social media's important role in everybody's life. As the social media includes the web technologies that enable us to communicate directly and to modify user-generated content, the adoption...
As most approaches perform social network analysis from a static point of view, our paper is centered on the analysis of the Twitter network, emphasizing its dynamic aspects by using an analytics and visualization-centered application. Our aim is to model the activity and importance of individual users over time, as well as the connection between a recent activity of the entire network and on a given...
Starting from dialogism in which every act is perceived as a dialogue, we shift the perspective towards multi-participant chat conversations from Computer Supported Collaborative Learning in which ideas, points of view or more generally put voices interact, inter-animate and generate the context of a conversation. Within this perspective of discourse analysis, we introduce an implemented framework,...
Every person is unique and has different sets of individual traits and characteristics. Although people possess different types of personalities, in the end they manage to understand each other and interact regardless of these differences. Starting from the simplest language elements, a simple remark is that, in general, people use certain words more frequently than others. These words might reveal...
Selfish nodes in an opportunistic network are nodes that do not want to participate in the routing process for various reasons, such as low resources (e.g. battery, memory, CPU, network or bandwidth), fear of malicious data from unknown users, or even lack of interest in helping nodes from other communities. This may lead to messages sent in the network being delayed or even lost. Therefore, these...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.