Ingmar Weber
Dados Biográficos
| ID | 3583310 |
|---|---|
| NOME | Ingmar Weber |
| PRENOMES | Ingmar |
| SOBRENOME | Weber |
| ASSINATURA | WEBER I |
| AFILIAÇÕES | Saarland University |
| ORCID | 0000-0003-4169-2579 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 21 |
| TOTAL DE CITAÇÕES | 157 |
| TOTAL COMO AUTOR | 21 |
| TOTAL COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 2012 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2026 |
| ÍNDICE H | 6 |
The Grass Really is Greener on the Other Side
Immigration produces diverse outcomes, with some immigrants finding happiness in an improved quality of life, while others face emotional distress from unexpected challenges. Studying these emotional experiences is challenging due to limited longitudinal data. To address this, we curated high-quality data and analyzed Twitter activities of immigrants in the United States to explore how their expressed sentiments evolve post-migration, comparing t…
Integrating Traditional and Social Media Data to Predict Bilateral Migrant Stocks in the European Union
Although up-to-date information on the nature and extent of migration within the European Union (EU) is important for policymaking, timely and reliable statistics on the number of EU citizens residing in or moving across other member states are difficult to obtain. In this paper, we develop a statistical model that integrates data on EU migrant stocks using traditional sources such as census, population registers and Labour Force Survey, with nov…
Assessing Timely Migration Trends Through Digital Traces
Digital trace data presents an opportunity for promptly monitoring shifts in migrant populations. This contribution aims to determine whether the number of European migrants in the United Kingdom (UK) declined between March 2019 and March 2020, using weekly estimates derived from the Facebook Advertising Platform. The collected data is disaggregated according to age, level of education, and country of origin. To examine the fluctuation in the num…
Unveiling local patterns of child pornography consumption in France using Tor
Child pornography—better known as child sexual abuse material (CSAM)—represents a severe form of exploitation and victimization of children, leaving the victims with emotional and physical trauma. In this study, we aim to analyze local patterns of CSAM consumption across 1341 French communes in 20 metropolitan regions of France between March 16 to May 31, 2019 using fine-grained mobile traffic data of Tor network-related web services. We estimate…
Stop, in the Name of Covid! Using Social Media Data to Estimate the Effects of Covid-19-Related Travel Restrictions on Migration
In the wake of the COVID-19 pandemic, the International Organization for Migration has postulated that international migrant stocks fell short of their pre-pandemic projections by nearly 2 million as a result of travel restrictions. However, this decline is not testable with migration data from traditional sources. Key migration stakeholders have called for using data from alternative sources, including social media, to fill these gaps. Building …
Social capital mediates knowledge gaps in informing sexual and reproductive health behaviours across Africa
Advancing sexual and reproductive health is essential for promoting human rights and women's empowerment, and combating the HIV/AIDS epidemic. A large body of literature across the social sciences emphasizes the importance of social capital, generated through the strength of social networks, for shaping health behaviours. However, large-scale measurement of social capital and social networks remains elusive, especially in the context of low-incom…
Online social integration of migrants
As online social activities have become increasingly important for people’s lives, understanding how migrants integrate into online spaces is crucial for providing a more complete picture of integration processes. We curate a high-quality data set to quantify patterns of new online social connections among immigrants in the United States. Specifically, we focus on Twitter and leverage the unique features of these data, in combination with a prope…
Nowcasting Daily Population Displacement in Ukraine through Social Media Advertising Data
In times of crisis, real-time data mapping population displacements are invaluable for targeted humanitarian response. The Russian invasion of Ukraine on February 24, 2022, forcibly displaced millions of people from their homes including nearly 6 million refugees flowing across the border in just a few weeks, but information was scarce regarding displaced and vulnerable populations who remained inside Ukraine. We leveraged social media data from …
Perceptions of Fifa Men’s World Cup 2022 Host Nation Qatar in the Twittersphere
The FIFA Men’s World Cup Qatar 2022 has been analyzed through the frameworks of nation branding and soft power. As the world’s most popular sport event, the World Cup has the possibility to enhance host nations’ images internationally, but we are not aware of empirical work attempting to assess public perceptions of Qatar, despite the considerable attention it has been paid. Accordingly, we assessed the discussion in the Twittersphere to shed som…
Knowledge and Anxiety about Covid-19 in the State of Qatar, and the Middle East and North Africa Region—A Cross Sectional Study
While the coronavirus disease 2019 (COVID-19) pandemic wreaked havoc across the globe, we have witnessed substantial mis- and disinformation regarding various aspects of the disease. We conducted a cross-sectional study using a self-administered questionnaire for the general public (recruited via social media) and healthcare workers (recruited via email) from the State of Qatar, and the Middle East and North Africa region to understand the knowle…
Estimating Homophily in Social Networks Using Dyadic Predictions
Predictions of node categories are commonly used to estimate homophily and other relational properties in networks. However, little is known about the validity of using predictions for this task. We show that estimating homophily in a network is a problem of predicting categories of dyads (edges) in the graph. Homophily estimates are unbiased when predictions of dyad categories are unbiased. Node-level prediction models, such as the use of names …
A Framework for Estimating Migrant Stocks Using Digital Traces and Survey Data
An accurate estimation of international migration is hampered by a lack of timely and comprehensive data, and by the use of different definitions and measures of migration in different countries. In an effort to address this situation, we complement traditional data sources for the United Kingdom with social media data: our aim is to understand whether information from digital traces can help measure international migration. The Bayesian framewor…
Monitoring global digital gender inequality using the online populations of Facebook and Google
In recognition of the empowering potential of digital technologies, gender equality in internet access and digital skills is an important target in the United Nations (UN) Sustainable Development Goals (SDGs). Gender-disaggregated data on internet use are
Using Facebook ad data to track the global digital gender gap
Gender equality in access to the internet and mobile phones has become increasingly recognised as a development goal. Monitoring progress towards this goal however is challenging due to the limited availability of gender-disaggregated data, particularly in low-income countries. In this data sparse context, we examine the potential of a source of digital trace ‘big data’ – Facebook’s advertisement audience estimates – that provides aggregate data …
Political Fact-Checking on Twitter
Research suggests that fact checking corrections have only a limited impact on the spread of false rumors. However, research has not considered that fact-checking may be socially contingent, meaning there are social contexts in which truth may be more or less preferred. In particular, we argue that strong social connections between fact-checkers and rumor spreaders encourage the latter to prefer sharing accurate information, making them more like…
Automated Hate Speech Detection and the Problem of Offensive Language
A key challenge for automatic hate-speech detection on social media is the separation of hate speech from other instances of offensive language. Lexical detection methods tend to have low precision because they classify all messages containing particular terms as hate speech and previous work using supervised learning has failed to distinguish between the two categories. We used a crowd-sourced hate speech lexicon to collect tweets containing hat…
Leveraging Facebook's Advertising Platform to Monitor Stocks of Migrants
FailedRevolutions
Lately, the Islamic State of Iraq and Syria (ISIS) has managed to control large parts of Syria and Iraq. To better understand the roots of support for ISIS, we present a study using Twitter data. We collected a large number of Arabic tweets referring to ISIS and classified them as pro-ISIS or anti-ISIS. We then analyzed the historical timelines of both user groups and looked at their pre-ISIS period to gain insights into the antecedents of suppor…
Using Co-Following for Personalized Out-of-Context Twitter Friend Recommendation
We present two demos that give personalized `"out-of-context" recommendations of Twitter users to follow. By out-of-context we mean that a user wants to receive recommendation on, say, musicians to follow even though the user's tweets' contents and social links have no connection to the "context" of music. In this setting, where a user has never expressed interest in the context of music, many existing methods fail. Our approach exploits co-follo…
Quantifying Politics Using Online Data
Political Insights
We developed Political Insights, an online searchable database of politically charged queries, which allows you to obtain topical insights into partisan concern. In this paper we demonstrate how you can discover such political queries and how to lay bare which issues are most salient to political audiences. We employ anonymized search engine queries resulting in a click on U.S. political blogs to calculate the probability that a query will land o…
Political Fact-Checking on Twitter
Research suggests that fact checking corrections have only a limited impact on the spread of false rumors. However, research has not considered that fact-checking may be socially contingent, meaning there are social contexts in which truth may be more or less preferred. In particular, we argue that strong social connections between fact-checkers and rumor spreaders encourage the latter to prefer sharing accurate information, making them more like…
Leveraging Facebook's Advertising Platform to Monitor Stocks of Migrants
Using Facebook ad data to track the global digital gender gap
Gender equality in access to the internet and mobile phones has become increasingly recognised as a development goal. Monitoring progress towards this goal however is challenging due to the limited availability of gender-disaggregated data, particularly in low-income countries. In this data sparse context, we examine the potential of a source of digital trace ‘big data’ – Facebook’s advertisement audience estimates – that provides aggregate data …
Nowcasting Daily Population Displacement in Ukraine through Social Media Advertising Data
In times of crisis, real-time data mapping population displacements are invaluable for targeted humanitarian response. The Russian invasion of Ukraine on February 24, 2022, forcibly displaced millions of people from their homes including nearly 6 million refugees flowing across the border in just a few weeks, but information was scarce regarding displaced and vulnerable populations who remained inside Ukraine. We leveraged social media data from …
A Framework for Estimating Migrant Stocks Using Digital Traces and Survey Data
An accurate estimation of international migration is hampered by a lack of timely and comprehensive data, and by the use of different definitions and measures of migration in different countries. In an effort to address this situation, we complement traditional data sources for the United Kingdom with social media data: our aim is to understand whether information from digital traces can help measure international migration. The Bayesian framewor…
Monitoring global digital gender inequality using the online populations of Facebook and Google
In recognition of the empowering potential of digital technologies, gender equality in internet access and digital skills is an important target in the United Nations (UN) Sustainable Development Goals (SDGs). Gender-disaggregated data on internet use are
Assessing Timely Migration Trends Through Digital Traces
Digital trace data presents an opportunity for promptly monitoring shifts in migrant populations. This contribution aims to determine whether the number of European migrants in the United Kingdom (UK) declined between March 2019 and March 2020, using weekly estimates derived from the Facebook Advertising Platform. The collected data is disaggregated according to age, level of education, and country of origin. To examine the fluctuation in the num…
Stop, in the Name of Covid! Using Social Media Data to Estimate the Effects of Covid-19-Related Travel Restrictions on Migration
In the wake of the COVID-19 pandemic, the International Organization for Migration has postulated that international migrant stocks fell short of their pre-pandemic projections by nearly 2 million as a result of travel restrictions. However, this decline is not testable with migration data from traditional sources. Key migration stakeholders have called for using data from alternative sources, including social media, to fill these gaps. Building …
Integrating Traditional and Social Media Data to Predict Bilateral Migrant Stocks in the European Union
Although up-to-date information on the nature and extent of migration within the European Union (EU) is important for policymaking, timely and reliable statistics on the number of EU citizens residing in or moving across other member states are difficult to obtain. In this paper, we develop a statistical model that integrates data on EU migrant stocks using traditional sources such as census, population registers and Labour Force Survey, with nov…
Online social integration of migrants
As online social activities have become increasingly important for people’s lives, understanding how migrants integrate into online spaces is crucial for providing a more complete picture of integration processes. We curate a high-quality data set to quantify patterns of new online social connections among immigrants in the United States. Specifically, we focus on Twitter and leverage the unique features of these data, in combination with a prope…
Political Insights
We developed Political Insights, an online searchable database of politically charged queries, which allows you to obtain topical insights into partisan concern. In this paper we demonstrate how you can discover such political queries and how to lay bare which issues are most salient to political audiences. We employ anonymized search engine queries resulting in a click on U.S. political blogs to calculate the probability that a query will land o…
Quantifying Politics Using Online Data
Using Co-Following for Personalized Out-of-Context Twitter Friend Recommendation
We present two demos that give personalized `"out-of-context" recommendations of Twitter users to follow. By out-of-context we mean that a user wants to receive recommendation on, say, musicians to follow even though the user's tweets' contents and social links have no connection to the "context" of music. In this setting, where a user has never expressed interest in the context of music, many existing methods fail. Our approach exploits co-follo…
FailedRevolutions
Lately, the Islamic State of Iraq and Syria (ISIS) has managed to control large parts of Syria and Iraq. To better understand the roots of support for ISIS, we present a study using Twitter data. We collected a large number of Arabic tweets referring to ISIS and classified them as pro-ISIS or anti-ISIS. We then analyzed the historical timelines of both user groups and looked at their pre-ISIS period to gain insights into the antecedents of suppor…
Automated Hate Speech Detection and the Problem of Offensive Language
A key challenge for automatic hate-speech detection on social media is the separation of hate speech from other instances of offensive language. Lexical detection methods tend to have low precision because they classify all messages containing particular terms as hate speech and previous work using supervised learning has failed to distinguish between the two categories. We used a crowd-sourced hate speech lexicon to collect tweets containing hat…
Leveraging Facebook's Advertising Platform to Monitor Stocks of Migrants
Using Facebook ad data to track the global digital gender gap
Gender equality in access to the internet and mobile phones has become increasingly recognised as a development goal. Monitoring progress towards this goal however is challenging due to the limited availability of gender-disaggregated data, particularly in low-income countries. In this data sparse context, we examine the potential of a source of digital trace ‘big data’ – Facebook’s advertisement audience estimates – that provides aggregate data …
Political Fact-Checking on Twitter
Research suggests that fact checking corrections have only a limited impact on the spread of false rumors. However, research has not considered that fact-checking may be socially contingent, meaning there are social contexts in which truth may be more or less preferred. In particular, we argue that strong social connections between fact-checkers and rumor spreaders encourage the latter to prefer sharing accurate information, making them more like…
Monitoring global digital gender inequality using the online populations of Facebook and Google
In recognition of the empowering potential of digital technologies, gender equality in internet access and digital skills is an important target in the United Nations (UN) Sustainable Development Goals (SDGs). Gender-disaggregated data on internet use are
Knowledge and Anxiety about Covid-19 in the State of Qatar, and the Middle East and North Africa Region—A Cross Sectional Study
While the coronavirus disease 2019 (COVID-19) pandemic wreaked havoc across the globe, we have witnessed substantial mis- and disinformation regarding various aspects of the disease. We conducted a cross-sectional study using a self-administered questionnaire for the general public (recruited via social media) and healthcare workers (recruited via email) from the State of Qatar, and the Middle East and North Africa region to understand the knowle…
Estimating Homophily in Social Networks Using Dyadic Predictions
Predictions of node categories are commonly used to estimate homophily and other relational properties in networks. However, little is known about the validity of using predictions for this task. We show that estimating homophily in a network is a problem of predicting categories of dyads (edges) in the graph. Homophily estimates are unbiased when predictions of dyad categories are unbiased. Node-level prediction models, such as the use of names …
A Framework for Estimating Migrant Stocks Using Digital Traces and Survey Data
An accurate estimation of international migration is hampered by a lack of timely and comprehensive data, and by the use of different definitions and measures of migration in different countries. In an effort to address this situation, we complement traditional data sources for the United Kingdom with social media data: our aim is to understand whether information from digital traces can help measure international migration. The Bayesian framewor…
Perceptions of Fifa Men’s World Cup 2022 Host Nation Qatar in the Twittersphere
The FIFA Men’s World Cup Qatar 2022 has been analyzed through the frameworks of nation branding and soft power. As the world’s most popular sport event, the World Cup has the possibility to enhance host nations’ images internationally, but we are not aware of empirical work attempting to assess public perceptions of Qatar, despite the considerable attention it has been paid. Accordingly, we assessed the discussion in the Twittersphere to shed som…
Online social integration of migrants
As online social activities have become increasingly important for people’s lives, understanding how migrants integrate into online spaces is crucial for providing a more complete picture of integration processes. We curate a high-quality data set to quantify patterns of new online social connections among immigrants in the United States. Specifically, we focus on Twitter and leverage the unique features of these data, in combination with a prope…
Nowcasting Daily Population Displacement in Ukraine through Social Media Advertising Data
In times of crisis, real-time data mapping population displacements are invaluable for targeted humanitarian response. The Russian invasion of Ukraine on February 24, 2022, forcibly displaced millions of people from their homes including nearly 6 million refugees flowing across the border in just a few weeks, but information was scarce regarding displaced and vulnerable populations who remained inside Ukraine. We leveraged social media data from …
Unveiling local patterns of child pornography consumption in France using Tor
Child pornography—better known as child sexual abuse material (CSAM)—represents a severe form of exploitation and victimization of children, leaving the victims with emotional and physical trauma. In this study, we aim to analyze local patterns of CSAM consumption across 1341 French communes in 20 metropolitan regions of France between March 16 to May 31, 2019 using fine-grained mobile traffic data of Tor network-related web services. We estimate…
Stop, in the Name of Covid! Using Social Media Data to Estimate the Effects of Covid-19-Related Travel Restrictions on Migration
In the wake of the COVID-19 pandemic, the International Organization for Migration has postulated that international migrant stocks fell short of their pre-pandemic projections by nearly 2 million as a result of travel restrictions. However, this decline is not testable with migration data from traditional sources. Key migration stakeholders have called for using data from alternative sources, including social media, to fill these gaps. Building …
Social capital mediates knowledge gaps in informing sexual and reproductive health behaviours across Africa
Advancing sexual and reproductive health is essential for promoting human rights and women's empowerment, and combating the HIV/AIDS epidemic. A large body of literature across the social sciences emphasizes the importance of social capital, generated through the strength of social networks, for shaping health behaviours. However, large-scale measurement of social capital and social networks remains elusive, especially in the context of low-incom…
Integrating Traditional and Social Media Data to Predict Bilateral Migrant Stocks in the European Union
Although up-to-date information on the nature and extent of migration within the European Union (EU) is important for policymaking, timely and reliable statistics on the number of EU citizens residing in or moving across other member states are difficult to obtain. In this paper, we develop a statistical model that integrates data on EU migrant stocks using traditional sources such as census, population registers and Labour Force Survey, with nov…
Assessing Timely Migration Trends Through Digital Traces
Digital trace data presents an opportunity for promptly monitoring shifts in migrant populations. This contribution aims to determine whether the number of European migrants in the United Kingdom (UK) declined between March 2019 and March 2020, using weekly estimates derived from the Facebook Advertising Platform. The collected data is disaggregated according to age, level of education, and country of origin. To examine the fluctuation in the num…
The Grass Really is Greener on the Other Side
Immigration produces diverse outcomes, with some immigrants finding happiness in an improved quality of life, while others face emotional distress from unexpected challenges. Studying these emotional experiences is challenging due to limited longitudinal data. To address this, we curated high-quality data and analyzed Twitter activities of immigrants in the United States to explore how their expressed sentiments evolve post-migration, comparing t…
Political science (14 obras) · Computer Science (12 obras) · Business (9 obras) · Economics (8 obras) · Social media (8 obras) · Geography (7 obras) · Psychology (7 obras) · Social Media and Politics (7 obras) · Sociology (7 obras) · World Wide Web (7 obras)