Paola Zola

Italian National Research Council | CNR · Institute for Informatics and Telematics IIT

The increasing impact of Web 2.0 involves a growing usage of slang, abbreviations, and emphasized words, which limit the performance of traditional natural language processing models. The state‐of‐the‐art Part‐of‐Speech (POS) taggers are often unable to assign a meaningful POS tag to all the words in a Web 2.0 text. To solve this limitation, we are...

We explore the effects of coordinated users (i.e., users characterized by an unexpected, suspicious, or exceptional similarity) in information spreading on Twitter by quantifying the efficacy of their tactics in deceiving feed algorithms to maximize information outreach. In particular, we investigate the behavior of coordinated accounts within a la...

The COVID-19 pandemic has led to a corresponding infodemic, emphasised by the use of social media as the primary communication channel during lockdowns. This study was aimed at finding the accounts that spread information in Italian on COVID-19, and how such information was propagated in the first Western country to face a lockdown. The presented a...

Purpose This paper aims to analyse stakeholder sentiment about the corporate social responsibility (CSR) actions implemented by Italian companies between February 20, 2020 and April 20, 2020, which was the first peak in the outbreak of the COVID-19 health emergency in Italy. Design/methodology/approach Using sentiment analysis, the impact of COVID...

In recent years, the use of social media has considerably increased interaction between the public sector and citizens. At the same time, environmental issues such as climate change are increasingly gaining importance in society. In such a scenario, local governments are called to engage and communicate with citizens on environmental issues and pol...

This paper addresses the nontrivial task of Twitter financial disambiguation (TFD), which is relevant to filter financial domain tweets (e.g., alloy steel or coffee prices) when no unique identifiers (e.g., cashtags) are adopted. To automate TFD, we propose a transfer learning approach that uses freely labeled news titles to train diverse one-class...

Tracking information diffusion is a non-trivial task and it has been widely studied across different domains and platforms. The advent of social media has led to even more challenges, given the higher speed of information propagation and the growing impact of social bots and anomalous accounts. Nevertheless, it is crucial to derive a trustworthy in...

User location data is valuable for diverse social media analytics. In this paper, we address the non-trivial task of estimating a worldwide city-level Twitter user location considering only historical tweets. We propose a purely unsupervised approach that is based on a synthetic geographic sampling of Google Trends (GT) city-level frequencies of tw...

In this work we propose a novel approach to estimate the home location of Twitter users. Given a list of Twitter users, we extract their timelines (up to 3,200) using the Twitter Application Programming Interface (API) service. We use Google Trends to obtain a list of cities in which the nouns of a specific Twitter user are more popular. Then, base...

Purpose Because of the expansion of the internet and Web 2.0 phenomenon, new challenges are emerging in the disclosure practises adopted by organisations in the public-sector. This study aims to examine local governments’ (LGOs) use of social media (SM) in disclosing environmental actions/plans/information as a new way to improve accountability to...

We address the diffusion of information about the COVID-19 with a massive data analysis on Twitter, Instagram, YouTube, Reddit and Gab. We analyze engagement and interest in the COVID-19 topic and provide a differential assessment on the evolution of the discourse on a global scale for each platform and their users. We fit information spreading wit...

The concept of sustainable development has become dominant in the current socio‐economic debate at the global level. In particular, environmental issues have become increasingly central in the action of all organisations: private, public, and hybrid. Analysing a sample of Italian public utilities, we studied the level of disclosure regarding enviro...

Part-of-speech (POS) tagging is the basis of many Natural Language Processing tasks and, nowadays, there exist several algorithms able to determine the POS tag for a specific word. However, the increasing usage of Internet and the explosion of blogs and microblogs changed the way people communicate, and POS taggers trained on structured corpora los...

Due to the expansion of Internet and Web 2.0 phenomenon, there is a growing interest in sentiment analysis of freely opinionated text. In this paper, we propose a novel cross-source cross-domain sentiment classification, in which cross-domain-labeled Web sources (Amazon and Tripadvisor) are used to train supervised learning models (including two de...