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deactivhatelab

Recognizing Hate with NLP: The Teaching Experience of the#DEACTIVHATELab in Italian High Schools

evalita-sardistance

evalita2023-haspeede3

evaluate_post_disaster_planning_with_social_medias

This repository contains python scripts used for research in the field evaluate post disaster planning with social medias

friends-and-enemies-of-clinton

Stance detection, the task of identifying the speaker's opinion towards a particular target, has attracted the attention of researchers. This paper describes a novel approach for detecting stance in Twitter. We define a set of features in order to consider the context surrounding a target of interest with the final aim of training a model for predicting the stance towards the mentioned targets. In particular, we are interested in investigating political debates in social media. For this reason we evaluated our approach focusing on two targets of the SemEval-2016 Task 6 on Detecting stance in tweets, which are related to the political campaign for the 2016 U.S. presidential elections: Hillary Clinton vs. Donald Trump. For the sake of comparison with the state of the art, we evaluated our model against the dataset released in the SemEval-2016 Task 6 shared task competition. Our results outperform the best ones obtained by participating teams, and show that information about enemies and friends of politicians help in detecting stance towards them.

happy-parents

The repository contains the gold corpus used for an exploration of Italian Twitter Data with sentiment analysis (Happy Parents’ Tweets).

itacos-at-ibereval2017

The paper describes the ITAcos submission for the Stance and Gender Detection in Tweets on Catalan Independence shared task. Concerning the detection of stance, we ranked as the first position in both languages outperforming the baselines; while in gender detection we ranked as fourth and third for Catalan and Spanish. Our approach is based on three diverse groups of features: stylistic, structural and context-based. We introduced two novel features that exploit significant characteristics conveyed by the presence of Twitter marks and URLs. The results of our experiments are promising and will lead to future tailoring of these two features in a finer grained manner. The used code are available in this repository.

leave-or-remain

mappa.controlodio.it

multilingualstancedetection

pan2021_hamor

polarization_of_emotional_engagement_in_social_media

This repository contains python script that can be use to anaysis twitter data. Starting from text file containing ids, those scripts gather new data.

pyshpgeocode

Python package for shapefile-based geocoding

show-geolocated-events

Web app realize with d3.j and angular.js. Select a date in a brush linechart and show on the map the geolocated events of the selected period.

some-topojson-maps

Some maps in topojson format

stance-evolution-and-twitter-interactions

textclassification

twitter-experiment

how to use the Twitter API with python 3

understanding_the_attraction_dynamics_of_geolocated_hashtags

code in: understanding the attraction dynamics of geolocated hashtags

wordup