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What Sentiment analysis is about to identifying and extract subjective

information from source materials.

Why Applying the Sentiment analysis, researchers tries to identify what is the

sentiment behind a text. The input of a sentiment algorithm is a written text

while the output is a classification.

How Statistical Natural Language Processing

Keywords Spotting

Lexical Affinity

Hand-Crafted Models

Sentiment Analysis

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Overview

User

Favorites

Number of Tweets

Retweets

Framework

Data Output

Adjusted Closing Price

30 days 120 keywords

~1.2 GB of data ~1M tweets

Data Mined

Social networking platform where

users interact among themselves

through messages long

140 characters.

Index considers the 100 largestcompanies among the NASDAQ

Composite’s list.

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Process Flow Overview

Se

ntim

et

An

aly

sis

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ClusteringOnce ranked all the users in terms of number of tweets tweeted during the month, we studied the

trend of the aggregated number of retweets and favorites each user got:

This graph has been the basis for the clustering process for the users we

realized on our dataset.

41% 19% 19% 21%

Bots

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SentimentOccasional Users

A quite large percentage of user’s accounts are fake

accounts are managed by those bots. They can be

created for different reasons: tweets specific contents,

retweet some kind of tweets or follow different user.

Number of tweets between 226 and 6662 tweets

They are users who usually do not tweet about market

related content. They tweeted by chance about these

topics during the month and they content has almost no

engagement.

Number of tweets between 1 and 6 tweets

Bot

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SentimentMagazines Influencers

The difference from bots is that behind every tweet there

is a person, or a group of persons, which professionally

work on the Twitter account of the

company/journal/magazine etc. They tweet quite often

and their content has high engagement.

Number of tweets between 46 and 225 tweets

they are single persons who work in the financial

market with different roles. They tweet by

themselves and few time per day or per month.

Their tweets has usually a very high engagement.

Number of tweets between 7 and 45 tweets

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Sentiment

Sentiment Sign Sentiment Volume

Generated by the following function:

X=∑{[Yi(+)xRP(Yi)] - [Yi(-)xRP(Yi)]}

Generated by the following function:

X=∑{[Yi(+)xRP(Yi)] + [Yi(-)xRP(Yi)]}

It is the difference between positive

and negative overall sentiment

generated by each tweet day by day.

It is the sum between positive and

negative overall sentiment generated by

each tweet day by day.

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Correlation Overview

The comparison between the Adj. Close trend and the trends of the 2 clusters

took into consideration plus their Aggregated trend. The graph takes also into

consideration the days when the stock market was closed(areas grayed out).

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CONCLUSIONS

Expand the length of

the period took into

consideration (at least a 3

months)

Expand the analysis also to

the other two clusters or to

focus it on our best

performing cluster:

Magazines

Adj. Close and

Influencers:

47.4%

Adj. Close and

Magazines:

68.4%

Further Researches

Try different approaches

to the sentiment analysis

(i.e. Keyword Spotting)

Adj. Close and

Aggregated:

63.2%