Difference between revisions of "User:Dalmeidad"

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===Thursday (7/5/18)===
 
===Thursday (7/5/18)===
 
* Started week 4 of Coursera
 
* Started week 4 of Coursera
−
 
  
 
===Friday (7/6/18)===
 
===Friday (7/6/18)===
Line 110: Line 109:
 
* Read different articles to see which parts of the text were more important to a sentiment score
 
* 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
 
* Started creating personalized sentiment analyzer using the Loughran and McDonald Sentiment Word List
 +
 +
===Wednesday (7/11/18)===
 +
* Researched creating sentiment analyzers
 +
* Worked on the sentiment analysis code
 +
 +
===Thursday (7/12/18)===
 +
* Met with Advisor
 +
* Worked on note sheet from readings
 +
* Started looking at Naive Bayes Classification tutorial
 +
 +
===Friday (7/11/18)===
 +
* Continued researching and understanding sentiment analysis model
  
 
==Week 7: July 16th, 2018==
 
==Week 7: July 16th, 2018==
 +
===Monday (7/16/18)===
 +
* Began working on Poster, formed template and structure
 +
* Decided with the limited time left in program, the creation of a personalized sentiment model is improbable
 +
 +
===Tuesday (7/17/18)===
 +
* Reviewed papers that I had read and updated summaries of them
 +
* Worked on the URL code in forecasting model
 +
 +
===Wednesday (7/18/18)===
 +
* Continued to work to get results in forecasting model
 +
 +
===Thursday (7/19/18)===
 +
* Added related works table to poster
 +
* Added ideas to most other sections of poster
 +
* Debugged the weighting of URL sentiment in model
 +
 +
===Friday (7/20/18)===
 +
* Finally obtained results and included them in poster
 +
* Began working to include URL sentiment on the better model developed last year
  
 
==Week 8: July 23rd, 2018==
 
==Week 8: July 23rd, 2018==
 +
===Monday (7/23/18)===
 +
* Finished up poster
 +
* Created structure for my paper and added a rough outline
 +
 +
===Tuesday (7/24/18)===
 +
* Looked at simply moving code into better model to obtain results
 +
* Tweaked code to try to get results
 +
 +
===Wednesday (7/25/18)===
 +
* Added rough introduction to paper
 +
* Worked on debugging code
 +
 +
===Thursday (7/26/18)===
 +
* Worked on debugging code
 +
 +
===Friday (7/27/18)===
 +
* Worked on debugging code
 +
* Added new sections to paper
  
 
==Week 9: July 30th, 2018==
 
==Week 9: July 30th, 2018==
 +
===Monday (7/30/18)===
 +
* Began final presentation preperation
 +
* Finally obtained results from better model, but results were unexpected, even from model without URL inclusion
 +
 +
===Tuesday (7/31/18)===
 +
* Finished presentation and practiced with fellow REU students
 +
* Worked on paper
 +
 +
===Wednesday (8/118)===
 +
* Final REU presentations
 +
 +
===Thursday (8/2/18)===
 +
* Worked on paper
 +
 +
===Friday (8/3/18)===
 +
* Worked on paper

Latest revision as of 16:21, 3 August 2018

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

Wednesday (7/11/18)

  • Researched creating sentiment analyzers
  • Worked on the sentiment analysis code

Thursday (7/12/18)

  • Met with Advisor
  • Worked on note sheet from readings
  • Started looking at Naive Bayes Classification tutorial

Friday (7/11/18)

  • Continued researching and understanding sentiment analysis model

Week 7: July 16th, 2018

Monday (7/16/18)

  • Began working on Poster, formed template and structure
  • Decided with the limited time left in program, the creation of a personalized sentiment model is improbable

Tuesday (7/17/18)

  • Reviewed papers that I had read and updated summaries of them
  • Worked on the URL code in forecasting model

Wednesday (7/18/18)

  • Continued to work to get results in forecasting model

Thursday (7/19/18)

  • Added related works table to poster
  • Added ideas to most other sections of poster
  • Debugged the weighting of URL sentiment in model

Friday (7/20/18)

  • Finally obtained results and included them in poster
  • Began working to include URL sentiment on the better model developed last year

Week 8: July 23rd, 2018

Monday (7/23/18)

  • Finished up poster
  • Created structure for my paper and added a rough outline

Tuesday (7/24/18)

  • Looked at simply moving code into better model to obtain results
  • Tweaked code to try to get results

Wednesday (7/25/18)

  • Added rough introduction to paper
  • Worked on debugging code

Thursday (7/26/18)

  • Worked on debugging code

Friday (7/27/18)

  • Worked on debugging code
  • Added new sections to paper

Week 9: July 30th, 2018

Monday (7/30/18)

  • Began final presentation preperation
  • Finally obtained results from better model, but results were unexpected, even from model without URL inclusion

Tuesday (7/31/18)

  • Finished presentation and practiced with fellow REU students
  • Worked on paper

Wednesday (8/118)

  • Final REU presentations

Thursday (8/2/18)

  • Worked on paper

Friday (8/3/18)

  • Worked on paper
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