This tool uses Natural Language Processing (NLP) to analyze sentiment from text. It works with any .csv or .xlsx file that has one column (no header), calculating the sentiment of each row. The results are visually presented, and can also be downloaded for external use. This is a scaled-down version of the Instagram Comment Scan AI, with reduced functionality.

To try out this tool, use the following temporary login credentials:

Free username: trial
Password: trial2024

This tool leverages Natural Language Processing (NLP) to examine comments and reactions to Instagram posts. It helps users easily understand audience sentiment, identify main topics of discussion, and spotlight the most impactful comments. All data is visualized for straightforward interpretation, but can also be downloaded for external use.

Running and maintaining this tool costs money, and is therefore is only available to paid subscribers (contact me to discuss trial access, or for academic use).

This tutorial will guide you through a scalable and profitable Machine Learning (ML) approach for inter-day stock trading using R. It is tailored for people with intermediate experience in R programming and machine learning.

Participant Visualizer

Recruiting participants from around the world?Visualize where your participants are from using this (free) web app. Either input county names and sample sizes directly, or upload a CSV.

Username: trial
Password: trial2024

Use this tool to highlight all the places you've explored. Download your map to easily share your adventures with others.

Free username: trial
Password: trial2024

ResearchLens (PDF): Discover key themes in academic research using PDF documents

This tool can be used to generate WordClouds from PDF versions of scientific papers. The R shiny app, and step-by-step tutorial can be found below

ResearchLens (via Google Scholar): Discover key themes in academic research using Google Scholar

This step-by-step tutorial explains how to create a WordCloud in R using a researcher’s name and their Google Scholar page.

(A web app is not available because the ScholaR package is not compatible with R Shiny)