Syntactic and Semantic Analysis and Visualization of Unstructured English Texts

People have complex thoughts, and they often express their thoughts with complex sentences using natural languages. This complexity may facilitate efficient communications among the audience with the same knowledge base. But on the other hand, for a different or new audience this composition becomes cumbersome to understand and analyze. Analysis of such compositions using syntactic or semantic measures is a challenging job and defines the base step for natural language processing. In this dissertation I explore and propose a number of new techniques to analyze and visualize the syntactic and semantic patterns of unstructured English texts. The syntactic analysis is done through a proposed visualization technique which categorizes and compares different English compositions based on their different reading complexity metrics. For the semantic analysis I use Latent Semantic Analysis (LSA) to analyze the hidden patterns in complex compositions. I have used this technique to analyze comments from a social visualization web site for detecting the irrelevant ones (e.g., spam). The patterns of collaborations are also studied through statistical analysis. Word sense disambiguation is used to figure out the correct sense of a word in a sentence or composition. Using textual similarity measure, based on the different word similarity measures and word sense disambiguation on collaborative text snippets from social collaborative environment, reveals a direction to untie the knots of complex hidden patterns of collaboration

Tell It Slant: Investigating the Engagement, Discourse, and Popularity of Data Visualization in Online Communities

Data visualizations are increasingly accessible to people online, often to non-specialized audiences. However, what we know about how people make sense of data and engage with the visualized content is typically limited to observations from controlled user studies, sometimes with highly-specialized participants. As a result, there is a limited vocabulary to describe how visualizations as a technique of information sharing permeate organic communities. This thesis investigates how data visualization systems infiltrate online social settings and characterizes the conditions under which users engage or do not engage with them. We captured conversations on Reddit from March 2, 2021 to December 31, 2021, collecting 993,018 discussion threads. We found that data visualizations constituted 0.0002% (217 out of 993,018) of all threads cataloged, with all visualizations originating from one of four news sources: The Washington Post, The New York Times, The Guardian, or CNN. Our analysis suggests that visual design did not impact discourse or popularity. Rather, our findings spotlight that visualizations are often part of a broader information ecosystem, and the visual features may have no measurable impact on long-term engagement

Representação dinâmica de dados de fontes heterogéneas

Mestrado em Engenharia de Computadores e TelemáticaEsta dissertação surge no contexto de Open Data. O objectivo é propor uma solução que permita às instituições que aderem a este princípio representar de forma dinâmica os dados disponibilizados, bem como compreender quais as diferenças na implementação dessa solução na representação de dados heterogéneos provenientes de uma só fonte e na representação de dados provenientes de fontes heterogéneas. Após uma apresentação do conceito de Open Data, dando-se a conhecer alguns portais web que o aplicam, bem como do conceito de Linked Open Data derivado do primeiro, são abordadas algumas técnicas e heurísticas que podem ser utilizadas na criação de visualizações gráficas de dados, apresentando-se também algumas ferramentas que podem ser utilizadas para esse fim. Nesta dissertação procura-se ainda dar a conhecer algumas ferramentas que podem ser utilizadas na criação de reports. O cenário utilizado para o desenvolvimento desta solução foi a Universidade de Aveiro, sendo que o mesmo permitiu a criação de um protótipo para uma aplicação que possibilita a representação e visualização de forma dinâmica dos dados facultados por esta instituição por meio de tabelas, gráficos e reports, independentemente da proveniência dos mesmos.This dissertation is inserted in the Open Data context. Its objective is to propose a solution that allows institutions adherent to this principle the ability to represent data in a dynamic fashion, as well as to understand the main differences in the implementation of this solution for the representation of heterogeneous data from only one source and the representation of data from heterogeneous sources. After a presentation of the Open Data and Linked Open Data concepts, enumerating some web portals that apply these principles, some techniques and heuristics that can be used in the creation of graphic data visualizations, as well as some tools that can be used to this end are described. Also, some tools that permit the creation of reports are described in this dissertation. The scenario used to develop this solution was Aveiro University. This allowed the creation of a prototype application that permits the dynamic representation and visualization of data provided by this institution by means of tables, charts and reports, independently of its source