Dogecoin Twitter Sentiment Analysis (5000 Tweet Sample June 26-28)

Dogecoin price movement is often considered to be influenced by Twitter sentiment, particularly from so-called "Whales", or influential people, such as Elon Musk.  Through data collection and machine learning, we can aggregate twitter posts within a specific time frame and analyze the sentiment of those posts algorithmically. I randomly scraped 5000 tweets posted between June 26th and June 28th that had the word or tag "dogecoin" in them. I then imported the tweets into a DataFrame in Python for analysis.  There are a variety of word and sentence-based tokenizers that machine learning practitioners use to prepare the text for machine learning models, but for time's sake, I used MonkeyLearn's API, which allows users to quickly analyze text sentiment using MonkeyLearn's pre-made text models.  The 5000 tweets in aggregate were classified as positive with a 93.3% confidence level.  This leads me to believe that over the past few days, the general Twitter sentiment around Dogecoin has been relatively positive. Of course, this is a very limited analysis, and more data and more specifically tuned models would be required to get a very accurate picture of Twitter sentiment. Furthermore, the extent to which Twitter sentiment influences future Dogecoin price movement is uncertain but certainly limited, especially when looking at Twitter posts in general rather than focusing on "Whales".

back
default-avatar-8

liamgentile

Jun 28, 2021

-22.09%

Change % Since Posting

0.26

Price When Posted

-0.06

Change Since Posting

DOGE

dogecoin

0.20

-0.00
-1.74%
Current Price

Dogecoin Twitter Sentiment Analysis (5000 Tweet Sample June 26-28)

bullish

Dogecoin price movement is often considered to be influenced by Twitter sentiment, particularly from so-called "Whales", or influential people, such as Elon Musk. 

Through data collection and machine learning, we can aggregate twitter posts within a specific time frame and analyze the sentiment of those posts algorithmically.

I randomly scraped 5000 tweets posted between June 26th and June 28th that had the word or tag "dogecoin" in them. I then imported the tweets into a DataFrame in Python for analysis. 

There are a variety of word and sentence-based tokenizers that machine learning practitioners use to prepare the text for machine learning models, but for time's sake, I used MonkeyLearn's API, which allows users to quickly analyze text sentiment using MonkeyLearn's pre-made text models. 

The 5000 tweets in aggregate were classified as positive with a 93.3% confidence level. 

This leads me to believe that over the past few days, the general Twitter sentiment around Dogecoin has been relatively positive. Of course, this is a very limited analysis, and more data and more specifically tuned models would be required to get a very accurate picture of Twitter sentiment. Furthermore, the extent to which Twitter sentiment influences future Dogecoin price movement is uncertain but certainly limited, especially when looking at Twitter posts in general rather than focusing on "Whales".

 

 

update-select
update-select
update-select
Comments

Write your comment....

Sign in to comment

read-time
1 min

0.30

Target Price

6/ 10

Confidence

< 1 Week

Timeframe
catalyst icon
Earnings Release
catalyst icon
News
catalyst icon
SEC Filing
catalyst icon
Sentiment
catalyst icon
Other Catalyst

DOGE Channel

Start new chat
aiodd-ad
next