Community and sentiment analysis based on tweets

Overview

Social Media Analytics project

Community and sentiment analysis based on tweets

The project has set itself the goal of analyzing the thoughts and interaction of Italian users through the social posts expressed through the Twitter platform on the day of the entry into force of the new measures. In particular, we want to research the reference hubs present on the network, but also the sentiment and emotions of peoples with respect to the new limitations.

Motivation

One of the hottest topics in Italy in the last months of 2021 concerns the introduction of the Super Green Pass to access indoor clubs, events, gyms, etc. This security measure entered into force on 6 December 2021 and in fact no longer allows access to various services to those who have not completed the vaccination cycle. For these reasons it was decided, for the development of the project, to analyze the impressions of the Italian Twitter community regarding the Super Green Pass, with the aim of understanding who are the users who write and interact on the platform and if there are specific communities among the users who have commented on the introduction of this extension. We also want to analyze the possible influencing nodes of the network and verify the sentiment around them.

Data

The data was collected by Twitter using their API and Tweepy python package. All tweets were written on December 6th in italian languages.
In data folder you can find the .csv file with all the collected tweet (here), and you can also find two extras files that contains the sentiment extracted for each tweet (here) and the aggregated sentiment per cluster (here).

Files

All the developed code is present in the file Code.ipynb. You can also find the report and presentation made for the exam. Both in italian language.

How to run code?

We advise you to run all the code in Google Colaboratory platform. All notebooks all already setted to import the necessary packages! If you have any doubt please feel free to contact me!

Graph visualization

In Pyvis_export folder you can find two exported interactive visualization of the network graph. You can also find a static version of the images in .jpg files if you want to see them quickly (html version is quite slow at opening).

Results

We have found that hubs are not famous people, this may be an expected result due to the particular context of the no-vax discussion. In this context, the ideas and contents are more important than the celebrity of the person.
Focusing on sentiment analysis we noticed that the vast majority of tweets are neutral or negative! This is a far cry from the reality where most people have been vaccinated and are not that disappointed with the new rules.

About us

Riccardo Confalonieri - Data Science Student @ University of Milano-Bicocca

Justin Armanini - Data Science Student @ University of Milano-Bicocca

Chiara Cormio - Data Science Student @ University of Milano-Bicocca

Owner
Computer Science Bachelor @ Università degli Studi Milano Bicocca. DataScience Student @ Università degli Studi Milano Bicocca.
DAGAN - Dual Attention GANs for Semantic Image Synthesis

Contents Semantic Image Synthesis with DAGAN Installation Dataset Preparation Generating Images Using Pretrained Model Train and Test New Models Evalu

Hao Tang 104 Oct 08, 2022
Retraining OpenAI's GPT-2 on Discord Chats

Train OpenAI's GPT-2 on Discord Chats Retraining a Text Generation Model on Discord Chats using gpt-2-simple that wraps existing model fine-tuning and

Ayush Mishra 4 Oct 27, 2022
2021搜狐校园文本匹配算法大赛baseline

sohu2021-baseline 2021搜狐校园文本匹配算法大赛baseline 简介 分享了一个搜狐文本匹配的baseline,主要是通过条件LayerNorm来增加模型的多样性,以实现同一模型处理不同类型的数据、形成不同输出的目的。 线下验证集F1约0.74,线上测试集F1约0.73。

苏剑林(Jianlin Su) 45 Sep 06, 2022
Dense Passage Retriever - is a set of tools and models for open domain Q&A task.

Dense Passage Retrieval Dense Passage Retrieval (DPR) - is a set of tools and models for state-of-the-art open-domain Q&A research. It is based on the

Meta Research 1.1k Jan 07, 2023
Quick insights from Zoom meeting transcripts using Graph + NLP

Transcript Analysis - Graph + NLP This program extracts insights from Zoom Meeting Transcripts (.vtt) using TigerGraph and NLTK. In order to run this

Advit Deepak 7 Sep 17, 2022
NLP applications using deep learning.

NLP-Natural-Language-Processing NLP applications using deep learning like text generation etc. 1- Poetry Generation: Using a collection of Irish Poem

KASHISH 1 Jan 27, 2022
Script to download some free japanese lessons in portuguse from NHK

Nihongo_nhk This is a script to download some free japanese lessons in portuguese from NHK. It can be executed by installing the packages with: pip in

Matheus Alves 2 Jan 06, 2022
A demo for end-to-end English and Chinese text spotting using ABCNet.

ABCNet_Chinese A demo for end-to-end English and Chinese text spotting using ABCNet. This is an old model that was trained a long ago, which serves as

Yuliang Liu 45 Oct 04, 2022
SAVI2I: Continuous and Diverse Image-to-Image Translation via Signed Attribute Vectors

SAVI2I: Continuous and Diverse Image-to-Image Translation via Signed Attribute Vectors [Paper] [Project Website] Pytorch implementation for SAVI2I. We

Qi Mao 44 Dec 30, 2022
Sequence model architectures from scratch in PyTorch

This repository implements a variety of sequence model architectures from scratch in PyTorch. Effort has been put to make the code well structured so that it can serve as learning material. The train

Brando Koch 11 Mar 28, 2022
BERT score for text generation

BERTScore Automatic Evaluation Metric described in the paper BERTScore: Evaluating Text Generation with BERT (ICLR 2020). News: Features to appear in

Tianyi 1k Jan 08, 2023
FireFlyer Record file format, writer and reader for DL training samples.

FFRecord The FFRecord format is a simple format for storing a sequence of binary records developed by HFAiLab, which supports random access and Linux

77 Jan 04, 2023
LCG T-TEST USING EUCLIDEAN METHOD

This project has been created for statistical usage, purposing for determining ATL takers and nontakers using LCG ttest and Euclidean Method, especially for internal business case in Telkomsel.

2 Jan 21, 2022
小布助手对话短文本语义匹配的一个baseline

oppo-text-match 小布助手对话短文本语义匹配的一个baseline 模型 参考:https://kexue.fm/archives/8213 base版本线下大概0.952,线上0.866(单模型,没做K-flod融合)。 训练 测试环境:tensorflow 1.15 + keras

苏剑林(Jianlin Su) 132 Dec 14, 2022
Repositório da disciplina no semestre 2021-2

Avisos! Nenhum aviso! Compiladores 1 Este é o Git da disciplina Compiladores 1. Aqui ficará o material produzido em sala de aula assim como tarefas, w

6 May 13, 2022
Research Code for NeurIPS 2020 Spotlight paper "Large-Scale Adversarial Training for Vision-and-Language Representation Learning": UNITER adversarial training part

VILLA: Vision-and-Language Adversarial Training This is the official repository of VILLA (NeurIPS 2020 Spotlight). This repository currently supports

Zhe Gan 109 Dec 31, 2022
PyTorch implementation of convolutional neural networks-based text-to-speech synthesis models

Deepvoice3_pytorch PyTorch implementation of convolutional networks-based text-to-speech synthesis models: arXiv:1710.07654: Deep Voice 3: Scaling Tex

Ryuichi Yamamoto 1.8k Dec 30, 2022
Unsupervised Abstract Reasoning for Raven’s Problem Matrices

Unsupervised Abstract Reasoning for Raven’s Problem Matrices This code is the implementation of our TIP paper. This is the first unsupervised abstract

Tao Zhuo 9 Dec 17, 2022
Code Implementation of "Learning Span-Level Interactions for Aspect Sentiment Triplet Extraction".

Span-ASTE: Learning Span-Level Interactions for Aspect Sentiment Triplet Extraction ***** New March 31th, 2022: Scikit-Style API for Easy Usage *****

Chia Yew Ken 111 Dec 23, 2022
Winner system (DAMO-NLP) of SemEval 2022 MultiCoNER shared task over 10 out of 13 tracks.

KB-NER: a Knowledge-based System for Multilingual Complex Named Entity Recognition The code is for the winner system (DAMO-NLP) of SemEval 2022 MultiC

116 Dec 27, 2022