This App collects comments and responses from a selected video through the API. It is possible to download the information in XLSX file, (Date, type of interaction (comment / response), author of the comment, user who responds, comments and respective response (s).

Additionally, the App returns a network type file (GEXF format) generated from user comments-responses. This GEXF file can be visualized in network analysis tools, such as NodeXL, Retina, Gephi-Lite, among others.

I am developing this App in Python

by Dr. Verónica Espinoza.

This is a word co-occurrence generator application.

It allows you to analyze text data and visualize the co-occurrence relationships between words.

The tool processes the input text, identifies word co-occurrences, and creates a network visualization.

You can customize parameters such as minimum co-occurrence, window size, and minimum word length.

Community Detection Algorithm: Louvain Algorithm.

Node Size Representation: Based on co-occurrence occurrences.

Layout Algorithms Available: Fruchterman-Reingold, Kamada-Kawai, Davidson-Harel, among others.

Download Options: Edges & Nodes in XLSX and GraphML format.

I am developing this App in R 

by Dr. Verónica Espinoza.

This tool provides five tabs with different visualizations and analyses:

▪Correlation Plot: Shows six different mosaic plots with a visual representation of the correlation matrix. The cells of these plots are colored based on the correlation value.

.▪Correlation Network: Displays three different types of correlation networks where each variable in the CSV file is represented as a node. Connections (edges) between nodes represent the calculated correlations. Negative correlations are shown in red, while positive correlations are shown in blue. The correlation is calculated using Pearson correlation. The user can filter the correlation values in order to visualize the desired edges in the networks. Additionally, it is possible to download the file in GRAPHML format to visualize it in another tool.

▪Edges: Presents an interactive table with the edges of the correlation network. These edges correspond to significant correlations (different from zero) between variables. The table provides information about the connected variables as well as the calculated correlation value for each connection. The user can download the edges table in XLSX format.

▪My Data Table: Displays a table with the data loaded from the CSV file.

▪Correlation Matrix: Presents an interactive table showing the correlation matrix between variables in the CSV file.

I am developing this App in R

by Dr. Verónica Espinoza.