M Iacu
Dados Biográficos
| ID | 272641 |
|---|---|
| NOME | M Iacu |
| PRENOMES | M |
| SOBRENOME | Iacu |
| ASSINATURA | IACU M |
| AFILIAÇÕES | University of Milan |
| ORCID | 0000-0002-4884-0047 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 16 |
| TOTAL DE CITAÇÕES | 158 |
| TOTAL COMO AUTOR | 16 |
| TOTAL COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 2009 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2026 |
| ÍNDICE H | 5 |
Migration mood and policy responsiveness
Mobility functional areas and Covid-19 spread
This work introduces a new concept of functional areas called Mobility Functional Areas (MFAs), i.e., the geographic zones highly interconnected according to the analysis of mobile positioning data. The MFAs do not coincide necessarily with administrative borders as they are built observing natural human mobility and, therefore, they can be used to inform, in a bottom-up approach, local transportation, spatial planning, health and economic polici…
A Japanese Subjective Well-Being Indicator Based on Twitter Data
This study presents for the first time the SWB-J index, a subjective well-being indicator for Japan based on Twitter data. The index is composed by eight dimensions of subjective well-being and is estimated relying on Twitter data by using human supervised sentiment analysis. The index is then compared with the analogous SWB-I index for Italy in order to verify possible analogies and cultural differences. Further, through structural equation mode…
Forecasting change in conflict fatalities with dynamic elastic net
This article illustrates an approach to forecasting change in conflict fatalities designed to address the complexity of the drivers and processes of armed conflicts. The design of this approach is based on two main choices. First, to account for the specificity of conflict drivers and processes over time and space, we model conflicts in each individual country separately. Second, we draw on an adaptive model—Dynamic Elastic Net, DynENet—which is …
Mobility in Blue-Green Spaces Does Not Predict Covid-19 Transmission
Mobility restrictions during the COVID-19 pandemic ostensibly prevented the public from transmitting the disease in public places, but they also hampered outdoor recreation, despite the importance of blue-green spaces (e.g., parks and natural areas) for physical and mental health. We assess whether restrictions on human movement, particularly in blue-green spaces, affected the transmission of COVID-19. Our assessment uses a spatially resolved dat…
Is Japanese Gendered Language used on Twitter? A Large Scale Study
This study analyzes the usage of Japanese gendered language on Twitter. Starting from a collection of 408 million Japanese tweets from 2015 till 2019 and an additional sample of 2355 manually classified Twitter accounts timelines into gender and categories (politicians, musicians, etc). A large scale textual analysis is performed on this corpus to identify and examine sentence-final particles (SFPs) and first-person pronouns appearing in the text…
Isis at Its Apogee
We analyze 26.2 million comments published in Arabic language on Twitter, from July 2014 to January 2015, when Islamic State of Iraq and Syria (ISIS)’s strength reached its peak and the group was prominently expanding the territorial area under its control. By doing that, we are able to measure the share of support and aversion toward the Islamic State within the online Arab communities. We then investigate two specific topics. First, by exploiti…
A Theory of Statistical Inference for Matching Methods in Causal Research
Researchers who generate data often optimize efficiency and robustness by choosing stratified over simple random sampling designs. Yet, all theories of inference proposed to justify matching methods are based on simple random sampling. This is all the more troubling because, although these theories require exact matching, most matching applications resort to some form of ex post stratification (on a propensity score, distance metric, or the covar…
First- and second-level agenda setting in the Twittersphere
The rise of social network sites reopened the debate on the ability of traditional media to influence public opinion and act as an agenda setter. To answer this question, the present paper investigates first-level and second-level agenda-setting effects in the online environment by focusing on two heated Italian political debates (the reform of public funding of parties and the debate over austerity). By employing innovative and efficient statist…
EU regional unemployment as a transnational matter
Measuring Idiosyncratic Happiness Through the Analysis of Twitter
Social Media e Sentiment Analysis
Due miliardi e mezzo di utenti internet, oltre un miliardo di account Facebook, 550 milioni di profili Twitter. Che parlano, discutono, si confrontano sui temi più svariati. Un flusso in continuo divenire di informazioni che dà sostanza ogni giorno al mondo dei Big Data. Ma come si analizza concretamente il “sentiment” della Rete? Quali sono i pregi e i limiti dei diversi metodi esistenti? E a quali domande possiamo dare una risposta? Dopo aver p…
Using Sentiment Analysis to Monitor Electoral Campaigns
In recent years, there has been an increasing attention in the literature on the possibility of analyzing social media as a useful complement to traditional off-line polls to monitor an electoral campaign. Some scholars claim that by doing so, we can also produce a forecast of the result. Relying on a proper methodology for sentiment analysis remains a crucial issue in this respect. In this work, we apply the supervised method proposed by Hopkins…
Every tweet counts? How sentiment analysis of social media can improve our knowledge of citizens’ political preferences with an application to Italy and France
The growing usage of social media by a wider audience of citizens sharply increases the possibility of investigating the web as a device to explore and track political preferences. In the present paper we apply a method recently proposed by other social scientists to three different scenarios, by analyzing on one side the online popularity of Italian political leaders throughout 2011, and on the other the voting intention of French Internet users…
Multivariate Matching Methods That Are Monotonic Imbalance Bounding
We introduce a new “Monotonic Imbalance Bounding” (MIB) class of matching methods for causal inference with a surprisingly large number of attractive statistical properties. MIB generalizes and extends in several new directions the only existing class, “Equal Percent Bias Reducing” (EPBR), which is designed to satisfy weaker properties and only in expectation. We also offer strategies to obtain specific members of the MIB class, and analyze in mo…
Cem
In this article, we introduce a Stata implementation of coarsened exact matching, a new method for improving the estimation of causal effects by reducing imbalance in covariates between treated and control groups. Coarsened exact matching is faster, is easier to use and understand, requires fewer assumptions, is more easily automated, and possesses more attractive statistical properties for many applications than do existing matching methods. In …
Every tweet counts? How sentiment analysis of social media can improve our knowledge of citizens’ political preferences with an application to Italy and France
The growing usage of social media by a wider audience of citizens sharply increases the possibility of investigating the web as a device to explore and track political preferences. In the present paper we apply a method recently proposed by other social scientists to three different scenarios, by analyzing on one side the online popularity of Italian political leaders throughout 2011, and on the other the voting intention of French Internet users…
A Theory of Statistical Inference for Matching Methods in Causal Research
Researchers who generate data often optimize efficiency and robustness by choosing stratified over simple random sampling designs. Yet, all theories of inference proposed to justify matching methods are based on simple random sampling. This is all the more troubling because, although these theories require exact matching, most matching applications resort to some form of ex post stratification (on a propensity score, distance metric, or the covar…
Using Sentiment Analysis to Monitor Electoral Campaigns
In recent years, there has been an increasing attention in the literature on the possibility of analyzing social media as a useful complement to traditional off-line polls to monitor an electoral campaign. Some scholars claim that by doing so, we can also produce a forecast of the result. Relying on a proper methodology for sentiment analysis remains a crucial issue in this respect. In this work, we apply the supervised method proposed by Hopkins…
First- and second-level agenda setting in the Twittersphere
The rise of social network sites reopened the debate on the ability of traditional media to influence public opinion and act as an agenda setter. To answer this question, the present paper investigates first-level and second-level agenda-setting effects in the online environment by focusing on two heated Italian political debates (the reform of public funding of parties and the debate over austerity). By employing innovative and efficient statist…
Measuring Idiosyncratic Happiness Through the Analysis of Twitter
Migration mood and policy responsiveness
Cem
In this article, we introduce a Stata implementation of coarsened exact matching, a new method for improving the estimation of causal effects by reducing imbalance in covariates between treated and control groups. Coarsened exact matching is faster, is easier to use and understand, requires fewer assumptions, is more easily automated, and possesses more attractive statistical properties for many applications than do existing matching methods. In …
Multivariate Matching Methods That Are Monotonic Imbalance Bounding
We introduce a new “Monotonic Imbalance Bounding” (MIB) class of matching methods for causal inference with a surprisingly large number of attractive statistical properties. MIB generalizes and extends in several new directions the only existing class, “Equal Percent Bias Reducing” (EPBR), which is designed to satisfy weaker properties and only in expectation. We also offer strategies to obtain specific members of the MIB class, and analyze in mo…
Every tweet counts? How sentiment analysis of social media can improve our knowledge of citizens’ political preferences with an application to Italy and France
The growing usage of social media by a wider audience of citizens sharply increases the possibility of investigating the web as a device to explore and track political preferences. In the present paper we apply a method recently proposed by other social scientists to three different scenarios, by analyzing on one side the online popularity of Italian political leaders throughout 2011, and on the other the voting intention of French Internet users…
Social Media e Sentiment Analysis
Due miliardi e mezzo di utenti internet, oltre un miliardo di account Facebook, 550 milioni di profili Twitter. Che parlano, discutono, si confrontano sui temi più svariati. Un flusso in continuo divenire di informazioni che dà sostanza ogni giorno al mondo dei Big Data. Ma come si analizza concretamente il “sentiment” della Rete? Quali sono i pregi e i limiti dei diversi metodi esistenti? E a quali domande possiamo dare una risposta? Dopo aver p…
Using Sentiment Analysis to Monitor Electoral Campaigns
In recent years, there has been an increasing attention in the literature on the possibility of analyzing social media as a useful complement to traditional off-line polls to monitor an electoral campaign. Some scholars claim that by doing so, we can also produce a forecast of the result. Relying on a proper methodology for sentiment analysis remains a crucial issue in this respect. In this work, we apply the supervised method proposed by Hopkins…
EU regional unemployment as a transnational matter
Measuring Idiosyncratic Happiness Through the Analysis of Twitter
First- and second-level agenda setting in the Twittersphere
The rise of social network sites reopened the debate on the ability of traditional media to influence public opinion and act as an agenda setter. To answer this question, the present paper investigates first-level and second-level agenda-setting effects in the online environment by focusing on two heated Italian political debates (the reform of public funding of parties and the debate over austerity). By employing innovative and efficient statist…
Isis at Its Apogee
We analyze 26.2 million comments published in Arabic language on Twitter, from July 2014 to January 2015, when Islamic State of Iraq and Syria (ISIS)’s strength reached its peak and the group was prominently expanding the territorial area under its control. By doing that, we are able to measure the share of support and aversion toward the Islamic State within the online Arab communities. We then investigate two specific topics. First, by exploiti…
A Theory of Statistical Inference for Matching Methods in Causal Research
Researchers who generate data often optimize efficiency and robustness by choosing stratified over simple random sampling designs. Yet, all theories of inference proposed to justify matching methods are based on simple random sampling. This is all the more troubling because, although these theories require exact matching, most matching applications resort to some form of ex post stratification (on a propensity score, distance metric, or the covar…
Is Japanese Gendered Language used on Twitter? A Large Scale Study
This study analyzes the usage of Japanese gendered language on Twitter. Starting from a collection of 408 million Japanese tweets from 2015 till 2019 and an additional sample of 2355 manually classified Twitter accounts timelines into gender and categories (politicians, musicians, etc). A large scale textual analysis is performed on this corpus to identify and examine sentence-final particles (SFPs) and first-person pronouns appearing in the text…
Mobility in Blue-Green Spaces Does Not Predict Covid-19 Transmission
Mobility restrictions during the COVID-19 pandemic ostensibly prevented the public from transmitting the disease in public places, but they also hampered outdoor recreation, despite the importance of blue-green spaces (e.g., parks and natural areas) for physical and mental health. We assess whether restrictions on human movement, particularly in blue-green spaces, affected the transmission of COVID-19. Our assessment uses a spatially resolved dat…
Mobility functional areas and Covid-19 spread
This work introduces a new concept of functional areas called Mobility Functional Areas (MFAs), i.e., the geographic zones highly interconnected according to the analysis of mobile positioning data. The MFAs do not coincide necessarily with administrative borders as they are built observing natural human mobility and, therefore, they can be used to inform, in a bottom-up approach, local transportation, spatial planning, health and economic polici…
A Japanese Subjective Well-Being Indicator Based on Twitter Data
This study presents for the first time the SWB-J index, a subjective well-being indicator for Japan based on Twitter data. The index is composed by eight dimensions of subjective well-being and is estimated relying on Twitter data by using human supervised sentiment analysis. The index is then compared with the analogous SWB-I index for Italy in order to verify possible analogies and cultural differences. Further, through structural equation mode…
Forecasting change in conflict fatalities with dynamic elastic net
This article illustrates an approach to forecasting change in conflict fatalities designed to address the complexity of the drivers and processes of armed conflicts. The design of this approach is based on two main choices. First, to account for the specificity of conflict drivers and processes over time and space, we model conflicts in each individual country separately. Second, we draw on an adaptive model—Dynamic Elastic Net, DynENet—which is …
Migration mood and policy responsiveness
Computer Science (13 obras) · Artificial Intelligence (7 obras) · Mathematics (7 obras) · Political science (6 obras) · Social media (6 obras) · Business (5 obras) · Econometrics (5 obras) · Statistics (5 obras) · World Wide Web (5 obras) · Geography (4 obras)