Tweet Analytics for Political Position Estimation
Citation:
Mitchell, Aoife and Esposito, Anna and Vogel, Carl, Tweet Analytics for Political Position Estimation, 12th IEEE International Conference on Cognitive Infocommuincations -- CogInfoCom2021, 2021, 1035-1042Download Item:
MEV-CIC2021-v3.pdf (Published (author's copy) - Peer Reviewed) 445.6Kb
Abstract:
An increasingly popular method of predicting
trends and forecasting voting outcomes is to create a prediction
model based on alignment of publicly available social media
content produced by voters with voting behaviours. This paper
aims to analyse whether Twitter data extracted from local Dublin
City Council members’ Twitter accounts in comparison with
corresponding Councillor and Motion data from the Council-
Tracker.ie website can be interpreted and used to create a model
to predict the voting outcome of local Dublin City Council
votes to pass motions. The aim was to explore whether through
utilising machine learning techniques along with natural language
processing techniques, reliable and data driven predictions can
be generated for policy-making proposals brought forward. The
acquired experimental results suggest that the approach used
was marginally adequate in supporting the proposed hypothesis,
although some interesting results were derived. Of the models
analysed the Decision Tree model produced the most accurate
results with an accuracy score of 0.71 (baseline: 0.63). Analysis of
the models and an ablation study showed that the features derived
from tweet texts and motion texts along with overall properties of
a Councillor’s twitter account were the most powerful indicators.
The behaviour of a tweet, such as its acquired number of favorites
or retweets, were not indicative of the results in both the random
forest model and decision tree model
Author's Homepage:
http://people.tcd.ie/vogelDescription:
PUBLISHED
Author: Vogel, Carl
Other Titles:
12th IEEE International Conference on Cognitive Infocommuincations -- CogInfoCom2021Type of material:
Conference PaperCollections:
Availability:
Full text availableKeywords:
Social media, Dublin City Council, Politics, TwitterSubject (TCD):
Digital Humanities , Computational Linguistics , Computational linguistics , Early adopters, Social media, Social networks, Twitter, Google+, Personality traits, Information, Rumor, Influence , Political Behavior , Political Behavior , Political Behaviour , Political Methodology , Political Psychology , Political behavior , computational linguistics , political science , text analyticsLicences: