Miguel E Roberts
Biographic Data
| ID | 95709 |
|---|---|
| NAME | Miguel E Roberts |
| GIVEN NAMES | Miguel E |
| FAMILY NAME | Roberts |
| SIGNATURE | ROBERTS M E |
| AFFILIATIONS | University of California San Diego |
| ORCID | 0000-0001-6900-4366 |
| VERIFIED | Yes |
| TOTAL WORKS | 30 |
| TOTAL CITATIONS | 1522 |
| AUTHOR COUNT | 30 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2006 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 12 |
Does the Community Understand the Community Guidelines
Amid continued public controversy and political debate about online speech governments and civil society have pushed social media platforms to increase transparency around how they regulate speech, through community guidelines and content moderation systems, to support users to hold companies accountable for content removals. But how well do users understand apply platform content rules? We report results of two complementary studies. In Study 1,…
Bystanders and Reporters: Who Acts Against Illegal Online Content
Harmful and illegal content on social media is widespread, but what should be taken down is widely disputed, creating ongoing challenges for resolving the tension between free speech and user safety. User reporting is a key mechanism for addressing such content, yet little is known about who reports, what motivates them, and how they compare to the general population. We study these questions using two datasets: (1) a unique survey with individua…
Addressing Missingness in Serialized Bureaucratic Data: The Case of Chinese Courts
Courts around the world are putting their data online, making information about caseloads, parties, and decisions available to the public. Yet, this data is far from complete, and often only reflects a portion of courts' dockets. We offer and validate a set of tools for leveraging serialized bureaucratic data from courts to estimate the proportion of cases available to the public and the time courts take to make decisions. Using data from more th…
Quantifying Narrative Similarity Across Languages
How can one understand the spread of ideas across text data? This is a key measurement problem in sociological inquiry, from the study of how interest groups shape media discourse, to the spread of policy across institutions, to the diffusion of organizational structures and institution themselves. To study how ideas and narratives diffuse across text, we must first develop a method to identify whether texts share the same information and narrati…
Acquiescence Bias Inflates Estimates of Conspiratorial Beliefs and Political Misperceptions
Scholars, pundits, and politicians use opinion surveys to study citizen beliefs about political facts, such as the current unemployment rate, and more conspiratorial beliefs, such as whether Barack Obama was born abroad. Many studies, however, ignore acquiescence-response bias, the tendency for survey respondents to endorse any assertion made in a survey question regardless of content. With new surveys fielding questions asked in recent scholarsh…
The Authoritarian Data Problem
As the race to develop artificial intelligence (AI) accelerates, access to more and higher quality data is becoming increasingly crucial for AI systems. Yet the search for more data for AI facilitates information flow between authoritarian and democratic states in a way that has important implications for the behavior and output of AI. In particular, the homogenization of data, through institutions such as censorship and propaganda in authoritari…
Machine Learning for Social Science: An Agnostic Approach
Social scientists are now in an era of data abundance, and machine learning tools are increasingly used to extract meaning from data sets both massive and small. We explain how the inclusion of machine learning in the social sciences requires us to rethink not only applications of machine learning methods but also best practices in the social sciences. In contrast to the traditional tasks for machine learning in computer science and statistics, w…
Mass Digitization of Chinese Court Decisions: How to Use Text as Data in the Field of Chinese Law
Since 2014, Chinese courts have placed tens of millions of court judgments online. We analyze the promise and pitfalls of using this new data source, highlighting takeaways for readers facing similar issues using other collections of legal texts. Drawing on 1,058,986 documents from Henan Province, we identify problems with missing data and call on scholars to treat variation in court disclosure rates as an urgent research question. We also outlin…
At Home and Abroad: The Use of Denial-of-service Attacks during Elections in Nondemocratic Regimes
In this article, we study the political use of denial-of-service (DoS) attacks, a particular form of cyberattack that disables web services by flooding them with high levels of data traffic. We argue that websites in nondemocratic regimes should be especially prone to this type of attack, particularly around political focal points such as elections. This is due to two mechanisms: governments employ DoS attacks to censor regime-threatening informa…
Resilience to Online Censorship
To what extent are Internet users resilient to online censorship? When does censorship influence consumption of information and when does it create backlash? Drawing on a growing literature on Internet users’ reactions to censorship, I posit that awareness of censorship, incentives to seek out information, and resources to circumvent censorship are essential to resilience to censorship. I describe how authoritarian regimes have adapted their stra…
Adjusting for Confounding with Text Matching
We identify situations in which conditioning on text can address confounding in observational studies. We argue that a matching approach is particularly well‐suited to this task, but existing matching methods are ill‐equipped to handle high‐dimensional text data. Our proposed solution is to estimate a low‐dimensional summary of the text and condition on this summary via matching. We propose a method of text matching, topical inverse regression ma…
Censorship's Effect on Incidental Exposure to Information: Evidence From Wikipedia
The fast-growing body of research on internet censorship has examined the effects of censoring selective pieces of political information and the unintended consequences of censorship of entertainment. However, we know very little about the broader consequences of coarse censorship or censorship that affects a large array of information such as an entire website or search engine. In this study, we use China's complete block of Chinese language Wik…
Machine behaviour
STM: An R Package for Structural Topic Models
This paper demonstrates how to use the R package stm for structural topic modeling. The structural topic model allows researchers to flexibly estimate a topic model that includes document-level metadata. Estimation is accomplished through a fast variational approximation. The stm package provides many useful features, including rich ways to explore topics, estimate uncertainty, and visualize quantities of interest.
What Makes Foreign Policy Teams Tick: Explaining Variation in Group Performance at Geopolitical Forecasting
When do groups—be they countries, administrations, or other organizations—more or less accurately understand the world around them and assess political choices? Some argue that group decision-making processes often fail due to biases induced by groupthink. Others argue that groups, by aggregating knowledge, are better at analyzing the foreign policy world. To advance knowledge about the intersection of politics and group decision making, this pap…
Censored: Distraction and Diversion Inside China's Great Firewall
A groundbreaking and surprising look at contemporary censorship in ChinaAs authoritarian governments around the world develop sophisticated technologies for controlling information, many observers have predicted that these controls would be ineffective because they are easily thwarted and evaded by savvy Internet users. In Censored, Margaret Roberts demonstrates that even censorship that is easy to circumvent can still be enormously effective. Ta…
What is Political Methodology
An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content
How Sudden Censorship Can Increase Access to Information
Conventional wisdom assumes that increased censorship will strictly decrease access to information. We delineate circumstances when increases in censorship expand access to information for a substantial subset of the population. When governments suddenly impose censorship on previously uncensored information, citizens accustomed to acquiring this information will be incentivized to learn methods of censorship evasion. These evasion tools provide …
Computer‐Assisted Keyword and Document Set Discovery from Unstructured Text
The (unheralded) first step in many applications of automated text analysis involves selecting keywords to choose documents from a large text corpus for further study. Although all substantive results depend on this choice, researchers usually pick keywords in ad hoc ways that are far from optimal and usually biased. Most seem to think that keyword selection is easy, since they do Google searches every day, but we demonstrate that humans perform …
From Liberation to Turmoil: Social Media And Democracy
How can one technology—social media—simultaneously give rise to hopes for liberation in authoritarian regimes, be used for repression by these same regimes, and be harnessed by antisystem actors in democracy? We present a simple framework for reconciling these contradictory developments based on two propositions: 1) that social media give voice to those previously excluded from political discussion by traditional media, and 2) that although socia…
How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, Not Engaged Argument
The Chinese government has long been suspected of hiring as many as 2 million people to surreptitiously insert huge numbers of pseudonymous and other deceptive writings into the stream of real social media posts, as if they were the genuine opinions of ordinary people. Many academics, and most journalists and activists, claim that these so-called 50c party posts vociferously argue for the government's side in political and policy debates. As we s…
A Model of Text for Experimentation in the Social Sciences
Statistical models of text have become increasingly popular in statistics and computer science as a method of exploring large document collections. Social scientists often want to move beyond exploration, to measurement and experimentation, and make inference about social and political processes that drive discourse and content. In this article, we develop a model of text data that supports this type of substantive research. Our approach is to po…
Computational Social Science: Discovery and Prediction
Quantitative research in social science research is changing rapidly. Researchers have vast and complex arrays of data with which to work: we have incredible tools to sift through the data and recognize patterns in that data; there are now many sophisticated models that we can use to make sense of those patterns; and we have extremely powerful computational systems that help us accomplish these tasks quickly. This book focuses on some of the extr…
Introduction to the Virtual Issue: Recent Innovations in Text Analysis for Social Science
An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button
How Robust Standard Errors Expose Methodological Problems They Do Not Fix, and What to Do About It
Robust standard errors” are used in a vast array of scholarship to correct standard errors for model misspecification. However, when misspecification is bad enough to make classical and robust standard errors diverge, assuming that it is nevertheless not so bad as to bias everything else requires considerable optimism. And even if the optimism is warranted, settling for a misspecified model, with or without robust standard errors, will still bias…
Structural Topic Models for Open‐Ended Survey Responses
Collection and especially analysis of open‐ended survey responses are relatively rare in the discipline and when conducted are almost exclusively done through human coding. We present an alternative, semiautomated approach, the structural topic model (STM) (Roberts, Stewart, and Airoldi 2013; Roberts et al. 2013), that draws on recent developments in machine learning based analysis of textual data. A crucial contribution of the method is that it …
How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, Not Engaged Argument
The Chinese government has long been suspected of hiring as many as 2 million people to surreptitiously insert huge numbers of pseudonymous and other deceptive writings into the stream of real social media posts, as if they were the genuine opinions of ordinary people. Many academics, and most journalists and activists, claim that these so-called 50c party posts vociferously argue for the government's side in political and policy debates. As we s…
Computer-Assisted Text Analysis for Comparative Politics
Recent advances in research tools for the systematic analysis of textual data are enabling exciting new research throughout the social sciences. For comparative politics, scholars who are often interested in non-English and possibly multilingual textual datasets, these advances may be difficult to access. This article discusses practical issues that arise in the processing, management, translation, and analysis of textual data with a particular f…
From Liberation to Turmoil: Social Media And Democracy
How can one technology—social media—simultaneously give rise to hopes for liberation in authoritarian regimes, be used for repression by these same regimes, and be harnessed by antisystem actors in democracy? We present a simple framework for reconciling these contradictory developments based on two propositions: 1) that social media give voice to those previously excluded from political discussion by traditional media, and 2) that although socia…
Machine Learning for Social Science: An Agnostic Approach
Social scientists are now in an era of data abundance, and machine learning tools are increasingly used to extract meaning from data sets both massive and small. We explain how the inclusion of machine learning in the social sciences requires us to rethink not only applications of machine learning methods but also best practices in the social sciences. In contrast to the traditional tasks for machine learning in computer science and statistics, w…
How Robust Standard Errors Expose Methodological Problems They Do Not Fix, and What to Do About It
Robust standard errors” are used in a vast array of scholarship to correct standard errors for model misspecification. However, when misspecification is bad enough to make classical and robust standard errors diverge, assuming that it is nevertheless not so bad as to bias everything else requires considerable optimism. And even if the optimism is warranted, settling for a misspecified model, with or without robust standard errors, will still bias…
How Sudden Censorship Can Increase Access to Information
Conventional wisdom assumes that increased censorship will strictly decrease access to information. We delineate circumstances when increases in censorship expand access to information for a substantial subset of the population. When governments suddenly impose censorship on previously uncensored information, citizens accustomed to acquiring this information will be incentivized to learn methods of censorship evasion. These evasion tools provide …
Resilience to Online Censorship
To what extent are Internet users resilient to online censorship? When does censorship influence consumption of information and when does it create backlash? Drawing on a growing literature on Internet users’ reactions to censorship, I posit that awareness of censorship, incentives to seek out information, and resources to circumvent censorship are essential to resilience to censorship. I describe how authoritarian regimes have adapted their stra…
Computer‐Assisted Keyword and Document Set Discovery from Unstructured Text
The (unheralded) first step in many applications of automated text analysis involves selecting keywords to choose documents from a large text corpus for further study. Although all substantive results depend on this choice, researchers usually pick keywords in ad hoc ways that are far from optimal and usually biased. Most seem to think that keyword selection is easy, since they do Google searches every day, but we demonstrate that humans perform …
Adjusting for Confounding with Text Matching
We identify situations in which conditioning on text can address confounding in observational studies. We argue that a matching approach is particularly well‐suited to this task, but existing matching methods are ill‐equipped to handle high‐dimensional text data. Our proposed solution is to estimate a low‐dimensional summary of the text and condition on this summary via matching. We propose a method of text matching, topical inverse regression ma…
Mass Digitization of Chinese Court Decisions: How to Use Text as Data in the Field of Chinese Law
Since 2014, Chinese courts have placed tens of millions of court judgments online. We analyze the promise and pitfalls of using this new data source, highlighting takeaways for readers facing similar issues using other collections of legal texts. Drawing on 1,058,986 documents from Henan Province, we identify problems with missing data and call on scholars to treat variation in court disclosure rates as an urgent research question. We also outlin…
Acquiescence Bias Inflates Estimates of Conspiratorial Beliefs and Political Misperceptions
Scholars, pundits, and politicians use opinion surveys to study citizen beliefs about political facts, such as the current unemployment rate, and more conspiratorial beliefs, such as whether Barack Obama was born abroad. Many studies, however, ignore acquiescence-response bias, the tendency for survey respondents to endorse any assertion made in a survey question regardless of content. With new surveys fielding questions asked in recent scholarsh…
At Home and Abroad: The Use of Denial-of-service Attacks during Elections in Nondemocratic Regimes
In this article, we study the political use of denial-of-service (DoS) attacks, a particular form of cyberattack that disables web services by flooding them with high levels of data traffic. We argue that websites in nondemocratic regimes should be especially prone to this type of attack, particularly around political focal points such as elections. This is due to two mechanisms: governments employ DoS attacks to censor regime-threatening informa…
The Authoritarian Data Problem
As the race to develop artificial intelligence (AI) accelerates, access to more and higher quality data is becoming increasingly crucial for AI systems. Yet the search for more data for AI facilitates information flow between authoritarian and democratic states in a way that has important implications for the behavior and output of AI. In particular, the homogenization of data, through institutions such as censorship and propaganda in authoritari…
What Makes Foreign Policy Teams Tick: Explaining Variation in Group Performance at Geopolitical Forecasting
When do groups—be they countries, administrations, or other organizations—more or less accurately understand the world around them and assess political choices? Some argue that group decision-making processes often fail due to biases induced by groupthink. Others argue that groups, by aggregating knowledge, are better at analyzing the foreign policy world. To advance knowledge about the intersection of politics and group decision making, this pap…
Introduction to the Virtual Issue: Recent Innovations in Text Analysis for Social Science
An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button
No! Formal Theory, Causal Inference, and Big Data Are Not Contradictory Trends in Political Science
An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content
What is Political Methodology
An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content
Censorship's Effect on Incidental Exposure to Information: Evidence From Wikipedia
The fast-growing body of research on internet censorship has examined the effects of censoring selective pieces of political information and the unintended consequences of censorship of entertainment. However, we know very little about the broader consequences of coarse censorship or censorship that affects a large array of information such as an entire website or search engine. In this study, we use China's complete block of Chinese language Wik…
Development of a Scale to Assess Hwa-Byung, a Korean Culture-bound Syndrome, Using the Korean MMPI-2
This study documents the development of an MMPI-2 scale designed to assess features of the Korean culture-bound syndrome, Hwa-Byung (HB). An American research team and psychiatric practitioners in Korea created an 18-item HB scale via rational item selection and psycho-metric refinement. Principal components analysis of scale items revealed four components, reflecting content domains of general health, gastrointestinal symptoms, hopelessness, and…
Development of a Scale to Assess Hwa-Byung, a Korean Culture-bound Syndrome, Using the Korean MMPI-2
This study documents the development of an MMPI-2 scale designed to assess features of the Korean culture-bound syndrome, Hwa-Byung (HB). An American research team and psychiatric practitioners in Korea created an 18-item HB scale via rational item selection and psycho-metric refinement. Principal components analysis of scale items revealed four components, reflecting content domains of general health, gastrointestinal symptoms, hopelessness, and…
Reverse-engineering censorship in China: Randomized experimentation and participant observation
Censorship of social media in China Figuring out how many and which social media comments are censored by governments is difficult because those comments, by definition, cannot be read. King et al. have posted comments to social media sites in China and then waited to see which of these never appeared, which appeared and were then removed, and which appeared and survived. About 40% of their submissions were reviewed by an army of censors, and mor…
Structural Topic Models for Open‐Ended Survey Responses
Collection and especially analysis of open‐ended survey responses are relatively rare in the discipline and when conducted are almost exclusively done through human coding. We present an alternative, semiautomated approach, the structural topic model (STM) (Roberts, Stewart, and Airoldi 2013; Roberts et al. 2013), that draws on recent developments in machine learning based analysis of textual data. A crucial contribution of the method is that it …
How Robust Standard Errors Expose Methodological Problems They Do Not Fix, and What to Do About It
Robust standard errors” are used in a vast array of scholarship to correct standard errors for model misspecification. However, when misspecification is bad enough to make classical and robust standard errors diverge, assuming that it is nevertheless not so bad as to bias everything else requires considerable optimism. And even if the optimism is warranted, settling for a misspecified model, with or without robust standard errors, will still bias…
Computer-Assisted Text Analysis for Comparative Politics
Recent advances in research tools for the systematic analysis of textual data are enabling exciting new research throughout the social sciences. For comparative politics, scholars who are often interested in non-English and possibly multilingual textual datasets, these advances may be difficult to access. This article discusses practical issues that arise in the processing, management, translation, and analysis of textual data with a particular f…
No! Formal Theory, Causal Inference, and Big Data Are Not Contradictory Trends in Political Science
An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content
A Model of Text for Experimentation in the Social Sciences
Statistical models of text have become increasingly popular in statistics and computer science as a method of exploring large document collections. Social scientists often want to move beyond exploration, to measurement and experimentation, and make inference about social and political processes that drive discourse and content. In this article, we develop a model of text data that supports this type of substantive research. Our approach is to po…
Computational Social Science: Discovery and Prediction
Quantitative research in social science research is changing rapidly. Researchers have vast and complex arrays of data with which to work: we have incredible tools to sift through the data and recognize patterns in that data; there are now many sophisticated models that we can use to make sense of those patterns; and we have extremely powerful computational systems that help us accomplish these tasks quickly. This book focuses on some of the extr…
Introduction to the Virtual Issue: Recent Innovations in Text Analysis for Social Science
An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button
Computer‐Assisted Keyword and Document Set Discovery from Unstructured Text
The (unheralded) first step in many applications of automated text analysis involves selecting keywords to choose documents from a large text corpus for further study. Although all substantive results depend on this choice, researchers usually pick keywords in ad hoc ways that are far from optimal and usually biased. Most seem to think that keyword selection is easy, since they do Google searches every day, but we demonstrate that humans perform …
From Liberation to Turmoil: Social Media And Democracy
How can one technology—social media—simultaneously give rise to hopes for liberation in authoritarian regimes, be used for repression by these same regimes, and be harnessed by antisystem actors in democracy? We present a simple framework for reconciling these contradictory developments based on two propositions: 1) that social media give voice to those previously excluded from political discussion by traditional media, and 2) that although socia…
How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, Not Engaged Argument
The Chinese government has long been suspected of hiring as many as 2 million people to surreptitiously insert huge numbers of pseudonymous and other deceptive writings into the stream of real social media posts, as if they were the genuine opinions of ordinary people. Many academics, and most journalists and activists, claim that these so-called 50c party posts vociferously argue for the government's side in political and policy debates. As we s…
Censored: Distraction and Diversion Inside China's Great Firewall
A groundbreaking and surprising look at contemporary censorship in ChinaAs authoritarian governments around the world develop sophisticated technologies for controlling information, many observers have predicted that these controls would be ineffective because they are easily thwarted and evaded by savvy Internet users. In Censored, Margaret Roberts demonstrates that even censorship that is easy to circumvent can still be enormously effective. Ta…
What is Political Methodology
An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content
How Sudden Censorship Can Increase Access to Information
Conventional wisdom assumes that increased censorship will strictly decrease access to information. We delineate circumstances when increases in censorship expand access to information for a substantial subset of the population. When governments suddenly impose censorship on previously uncensored information, citizens accustomed to acquiring this information will be incentivized to learn methods of censorship evasion. These evasion tools provide …
Machine behaviour
STM: An R Package for Structural Topic Models
This paper demonstrates how to use the R package stm for structural topic modeling. The structural topic model allows researchers to flexibly estimate a topic model that includes document-level metadata. Estimation is accomplished through a fast variational approximation. The stm package provides many useful features, including rich ways to explore topics, estimate uncertainty, and visualize quantities of interest.
What Makes Foreign Policy Teams Tick: Explaining Variation in Group Performance at Geopolitical Forecasting
When do groups—be they countries, administrations, or other organizations—more or less accurately understand the world around them and assess political choices? Some argue that group decision-making processes often fail due to biases induced by groupthink. Others argue that groups, by aggregating knowledge, are better at analyzing the foreign policy world. To advance knowledge about the intersection of politics and group decision making, this pap…
Mass Digitization of Chinese Court Decisions: How to Use Text as Data in the Field of Chinese Law
Since 2014, Chinese courts have placed tens of millions of court judgments online. We analyze the promise and pitfalls of using this new data source, highlighting takeaways for readers facing similar issues using other collections of legal texts. Drawing on 1,058,986 documents from Henan Province, we identify problems with missing data and call on scholars to treat variation in court disclosure rates as an urgent research question. We also outlin…
At Home and Abroad: The Use of Denial-of-service Attacks during Elections in Nondemocratic Regimes
In this article, we study the political use of denial-of-service (DoS) attacks, a particular form of cyberattack that disables web services by flooding them with high levels of data traffic. We argue that websites in nondemocratic regimes should be especially prone to this type of attack, particularly around political focal points such as elections. This is due to two mechanisms: governments employ DoS attacks to censor regime-threatening informa…
Resilience to Online Censorship
To what extent are Internet users resilient to online censorship? When does censorship influence consumption of information and when does it create backlash? Drawing on a growing literature on Internet users’ reactions to censorship, I posit that awareness of censorship, incentives to seek out information, and resources to circumvent censorship are essential to resilience to censorship. I describe how authoritarian regimes have adapted their stra…
Adjusting for Confounding with Text Matching
We identify situations in which conditioning on text can address confounding in observational studies. We argue that a matching approach is particularly well‐suited to this task, but existing matching methods are ill‐equipped to handle high‐dimensional text data. Our proposed solution is to estimate a low‐dimensional summary of the text and condition on this summary via matching. We propose a method of text matching, topical inverse regression ma…
Censorship's Effect on Incidental Exposure to Information: Evidence From Wikipedia
The fast-growing body of research on internet censorship has examined the effects of censoring selective pieces of political information and the unintended consequences of censorship of entertainment. However, we know very little about the broader consequences of coarse censorship or censorship that affects a large array of information such as an entire website or search engine. In this study, we use China's complete block of Chinese language Wik…
Machine Learning for Social Science: An Agnostic Approach
Social scientists are now in an era of data abundance, and machine learning tools are increasingly used to extract meaning from data sets both massive and small. We explain how the inclusion of machine learning in the social sciences requires us to rethink not only applications of machine learning methods but also best practices in the social sciences. In contrast to the traditional tasks for machine learning in computer science and statistics, w…
Acquiescence Bias Inflates Estimates of Conspiratorial Beliefs and Political Misperceptions
Scholars, pundits, and politicians use opinion surveys to study citizen beliefs about political facts, such as the current unemployment rate, and more conspiratorial beliefs, such as whether Barack Obama was born abroad. Many studies, however, ignore acquiescence-response bias, the tendency for survey respondents to endorse any assertion made in a survey question regardless of content. With new surveys fielding questions asked in recent scholarsh…
Computer Science (23 works) · Political science (17 works) · Politics (17 works) · Law (14 works) · Computational and Text Analysis Methods (12 works) · Data science (10 works) · Mathematics (10 works) · Sociology (10 works) · World Wide Web (10 works) · Social Media and Politics (9 works)