Difference between revisions of "User:Dalmeidad"
From REU@MU
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===Friday (6/29/18)=== | ===Friday (6/29/18)=== | ||
| − | * | + | * Worked on week 3 of Coursera |
==Week 5: July 2nd, 2018== | ==Week 5: July 2nd, 2018== | ||
| + | ===Monday (7/2/18)=== | ||
| + | * Finished week 3 of Coursera | ||
| + | |||
| + | ===Tuesday (7/3/18)=== | ||
| + | * Added to code ability to export data taken from URL's into csv's | ||
| + | |||
| + | ===Wednesday (7/4/18)=== | ||
| + | * Brainstormed ways in which to include sentiment score from the URL's into the final prediction model | ||
| + | * LaTeX presentation, plus some further research to try to familiarize myself with it | ||
| + | |||
| + | ===Thursday (7/5/18)=== | ||
| + | * Started week 4 of Coursera | ||
| + | |||
| + | |||
| + | ===Friday (7/6/18)=== | ||
| + | * Worked on transferring files to lab computer and configuring applications to run sentiment extractor on them | ||
| + | * Read through 'Twitter Mood Predicts the Stock Market' and summarized | ||
==Week 6: July 9th, 2018== | ==Week 6: July 9th, 2018== | ||
| + | ===Monday (7/9/18)=== | ||
| + | * Began learning about tweepy and setting up a twitter application | ||
| + | * Finalized lab computer prep, just require certain packages to be installed | ||
| + | |||
| + | ===Tuesday (7/10/18)=== | ||
| + | * Read different articles to see which parts of the text were more important to a sentiment score | ||
| + | * Started creating personalized sentiment analyzer using the Loughran and McDonald Sentiment Word List | ||
==Week 7: July 16th, 2018== | ==Week 7: July 16th, 2018== | ||
Revision as of 15:49, 10 July 2018
Contents
Week 1: June 4th, 2018
Tuesday (6/5/18)
- Met with Dr. Praveen and Joe, discussed the outline of the project, as well as plans for week and other logistics
- Discussed overview of internship with Dr. Brylow, set up all of my accounts
- First read-through of the 2017 research paper of this topic - "Forecasting Stock Prices using Social Media Analysis"
Wednesday (6/6/18)
- Took notes on 2017 research paper, formulating initial questions and listing topic areas in which to focus on understanding
- Looked through last year's code
- Began reading through last year's references, starting with "Stock Market Prediction System with Modular Neural Networks"
Thursday (6/7/18)
- Met with Dr. Praveen and Joe, solidified ideas of what goals to consider for project
- Began making a research table, classifying readings through ideas/methods and conclusions
- Finished "Stock Market Prediction System with Modular Neural Networks" and added to table
- Finished half of week 1 of Coursera Data Science in Python
Friday (6/8/18)
- Built up basic knowledge about neural networks and the different types
- Brainstormed ways to approach last years project and improve upon it/ make it my own
Week 2: June 11th, 2018
Monday (6/11/18)
- Found around 8 papers pertaining to the project
- Created and filled out an excel spreadsheet covering the papers and their main ideas
Tuesday (6/12/18)
- Met with Dr. Praveen and Joe, solidified plans for bringing in other sources to make model better and considering N day look ahead
- Finished the papers found on Monday
- Started week 1 on Coursera
Wednesday (6/13/18)
- RCR training
Thursday (6/14/18)
- Met with Dr. Praveen briefly
- Finished week 1 Coursera
- Found more papers for background knowledge
- Worked on converting python 2.7 to python 3
Friday (6/15/18)
- Worked on better understanding pandas and other packages being used in previous year's code
- Started week 2 of Coursera
Week 3: June 18th, 2018
Monday (6/18/18)
- Met with P.H.D student Joseph Coelho and worked through Scott's code from last year's REU
- Continued to work independently on understanding the code
Tuesday (6/19/18)
- Met with Dr. Praveen and Joe, discussed the main goal and steps to take in improving the project
- Worked on making slight alterations the code and seeing the results
- Looked over some of the past readings I had done
Wednesday (6/20/18)
- Finished week 2 of Coursera
- Developed a plan as to how to implement changes to Scott's code in following weeks
Thursday (6/21/18)
- Worked on better understanding the method of finding and analyzing content of URLs in twits
Friday (6/22/18)
- Mostly added ability to parse to URLs
- Copied over Scott's code into a clean Jupyter Notebook and added important comments for myself
Week 4: June 25th, 2018
Monday (6/25/18)
- Finished the code to parse and obtain sentiment from URLs
- Began running tests, realized that running the code was very time consuming and began to look for a way around this
Tuesday (6/26/18)
- Met with Dr. Praveen and discussed my current progress on the code as well as steps to take during the coming weeks
- Began to write code to take all twit data and extract sentiment from the URLs, then save the data to a CSV file for future use
Wednesday (6/27/18)
- Worked on Midterm presentation
- Practiced Midterm presentation
Thursday (6/28/18)
- Presented and watched presentations of Midterm presentation
Friday (6/29/18)
- Worked on week 3 of Coursera
Week 5: July 2nd, 2018
Monday (7/2/18)
- Finished week 3 of Coursera
Tuesday (7/3/18)
- Added to code ability to export data taken from URL's into csv's
Wednesday (7/4/18)
- Brainstormed ways in which to include sentiment score from the URL's into the final prediction model
- LaTeX presentation, plus some further research to try to familiarize myself with it
Thursday (7/5/18)
- Started week 4 of Coursera
Friday (7/6/18)
- Worked on transferring files to lab computer and configuring applications to run sentiment extractor on them
- Read through 'Twitter Mood Predicts the Stock Market' and summarized
Week 6: July 9th, 2018
Monday (7/9/18)
- Began learning about tweepy and setting up a twitter application
- Finalized lab computer prep, just require certain packages to be installed
Tuesday (7/10/18)
- Read different articles to see which parts of the text were more important to a sentiment score
- Started creating personalized sentiment analyzer using the Loughran and McDonald Sentiment Word List
