[Automatic PR] Andreea Musulan

_posts/papers/2019-01-01-10.1177-2053168018816228.md

@@ -0,0 +1,22 @@
+---
+title: 'Politicians in the line of fire: Incivility and the treatment of women on
+  social media'
+venue: Research & Politics
+names: L. Rheault, Erica Rayment, Andreea Musulan
+tags:
+- Research & Politics
+link: https://doi.org/10.1177/2053168018816228
+author: Andreea Musulan
+categories: Publications
+
+---
+
+*{{ page.names }}*
+
+**{{ page.venue }}**
+
+{% include display-publication-links.html pub=page %}
+
+## Abstract
+
+A seemingly inescapable feature of the digital age is that people choosing to devote their lives to politics must now be ready to face a barrage of insults and disparaging comments targeted at them through social media. This article represents an effort to document this phenomenon systematically. We implement machine learning models to predict the incivility of about 2.2 m messages addressed to Canadian politicians and US Senators on Twitter. Specifically, we test whether women in politics are more heavily targeted by online incivility, as recent media reports suggested. Our estimates indicate that roughly 15% of public messages sent to Senators can be categorized as uncivil, whereas the proportion is about four points lower in Canada. We find evidence that women are more heavily targeted by uncivil messages than men, although only among highly visible politicians.

_posts/papers/2020-03-02-10.2139-ssrn.3547763.md

@@ -0,0 +1,21 @@
+---
+title: Investigating the Role of Social Bots During the 2019 Canadian Election
+venue: ''
+names: L. Rheault, Andreea Musulan
+tags:
+- ''
+link: https://doi.org/10.2139/ssrn.3547763
+author: Andreea Musulan
+categories: Publications
+
+---
+
+*{{ page.names }}*
+
+**{{ page.venue }}**
+
+{% include display-publication-links.html pub=page %}
+
+## Abstract
+
+Threats of social media manipulation during elections have become a central concern for modern democracies. The 2016 US election raised awareness of the problem and triggered a vigorous response from public agencies and social media companies around the globe. We contribute new evidence about the phenomenon by investigating the behavior of suspected social bots during the 2019 Canadian election, using a collection of 19.3 million messages posted by 1.8 million unique users on the Twitter platform. We ask three questions of interest. Have social bots influenced public sentiment toward party leaders during the campaign? Do social bots post content that differs substantively from the messages posted by regular, "human" users? And finally, is there evidence of foreign interference during the 2019 Canadian election? We find that social bots were disproportionately hostile to the incumbent prime minister Justin Trudeau. Our evidence suggests that social bots attempted to prolong the 'blackface' controversy afflicting the Trudeau campaign early on, but ultimately had no influence on public sentiment toward party leaders. While we detect clusters of social bots that are most likely foreign in origin, the general pattern appears more consistent with the idea that national partisan groups were the ones primarily making use of social bots for political influence.

_posts/papers/2020-07-06-10.1017-S0008423921000019.md

@@ -0,0 +1,21 @@
+---
+title: Explaining Support for COVID-19 Cell Phone Contact Tracing
+venue: Canadian Journal of Political Science/Revue canadienne de science politique
+names: L. Rheault, Andreea Musulan
+tags:
+- Canadian Journal of Political Science/Revue canadienne de science politique
+link: https://doi.org/10.1017/S0008423921000019
+author: Andreea Musulan
+categories: Publications
+
+---
+
+*{{ page.names }}*
+
+**{{ page.venue }}**
+
+{% include display-publication-links.html pub=page %}
+
+## Abstract
+
+Abstract Contact tracing applications have been deployed at a fast pace around the world to stop the spread of COVID-19 and may be key to containing future pandemics. This study aims to explain public opinion toward cell phone contact tracing using a survey experiment. We build upon a theory in evolutionary psychology—disease avoidance—to predict how media coverage of the pandemic affects public support for containment measures. We report three key findings. First, exposure to a news item that shows people ignoring social distancing rules causes an increase in support for cell phone contact tracing. Second, pre-treatment covariates such as anxiety and a belief that other people are not following the rules rank among the strongest predictors of support for COVID-19 apps. And third, while a majority of respondents approve of the reliance on cell phone contact tracing, concerns for rights and freedoms remain a salient preoccupation.

_posts/papers/2021-02-02-10.1080-19331681.2021.1879705.md

@@ -0,0 +1,22 @@
+---
+title: Efficient detection of online communities and social bot activity during electoral
+  campaigns
+venue: Journal of Information Technology & Politics
+names: L. Rheault, Andreea Musulan
+tags:
+- Journal of Information Technology & Politics
+link: https://doi.org/10.1080/19331681.2021.1879705
+author: Andreea Musulan
+categories: Publications
+
+---
+
+*{{ page.names }}*
+
+**{{ page.venue }}**
+
+{% include display-publication-links.html pub=page %}
+
+## Abstract
+
+ABSTRACT Threats of social media manipulation during elections have become a central concern for modern democracies. This study tackles the problem of identifying the purpose and origins of social bots during electoral campaigns. We propose a methodology – uniform manifold approximation and projection combined with user-level document embeddings – that efficiently reveals the community structure of social media users. We show that this method can be used to predict the partisan affiliation of social media users with high accuracy, detect anomalous concentrations of social bots, and infer their geographical origin. We illustrate the methodology using Twitter data from the 2019 Canadian electoral campaign. Our evidence supports the thesis that social bots have become an integral component of campaign strategy for national actors. We also demonstrate how the methodology can be deployed to identify clusters of foreign bots, and we show that such accounts were used to share far-right and environment-related content during the campaign.

_posts/papers/2022-01-01-10.2139-ssrn.4029114.md

@@ -0,0 +1,21 @@
+---
+title: The Winners and Losers of Rental Tribunals
+venue: Social Science Research Network
+names: Andreea Musulan
+tags:
+- Social Science Research Network
+link: https://doi.org/10.2139/ssrn.4029114
+author: Andreea Musulan
+categories: Publications
+
+---
+
+*{{ page.names }}*
+
+**{{ page.venue }}**
+
+{% include display-publication-links.html pub=page %}
+
+## Abstract
+
+None

records/semantic_paper_ids_ignored.json

@@ -55,6 +55,7 @@
   "259cf65eeae13861031f44cf906d43b155192b10",
   "2677f411aae496be93ee70bcbf0eb0e949c13e0c",
   "274a3340aa668667d68144385d12599003d76dde",
+  "2779a13bdcabe2f8ea3ca85a58504ef6d0b8388c",
   "27fd24efc03fc9ec548d9f32ba93542addb7f26b",
   "284aea8f6b61133f1db5e8cfc4eda80bc1e22882",
   "28761feb82f380379538ac108b3bb7515d90b042",
@@ -134,6 +135,7 @@
   "637242094e26e3f9c924f7782891d36b264520a7",
   "63c80e98e1548396201e8089eaf132b9a67951ba",
   "63f81ec1a331f66f8ced0c189bf30829fe017c1c",
+  "642c5c9588d50009dc840a68bd858cb78532e59e",
   "64530647d0fcdbfa96ed193f63194a71ebbff5f6",
   "64984d7e483303f1690b4dd0a4580dd4bf8cef95",
   "64b62ba1498ab2de3c0ae826069f55762ecdc56e",
@@ -151,6 +153,7 @@
   "6df1af429151da5f67173409ba564298fc551e60",
   "6e6983417939dbcb04a50a46a489ce6bbfe8aa9d",
   "6eaa91dcf32475434a38863d443d0bea0f40cbcf",
+  "6f0c7b376164a81895bc5c2bec106f0db6bd3142",
   "6f6e2e0311589a9af045f6acd00b7dee6d19fce4",
   "7269d4721ca2b6b555bee86aad97f562fa5cd9ac",
   "72d862256f707613a3c16cc79e490a69151d73bf",
@@ -236,6 +239,7 @@
   "ac2a659cc6f0e3635a9c1351c9963b47817205fb",
   "ad9232f48dc90540b28bbf3f3598dbc97d90b54f",
   "ada0dff98db47513a1659d078676c1671070c8ea",
+  "adbbe35ca11f6f9bdb9f0f2643ea87fc6a083b6b",
   "ae6b281e5732876ce72648c1440f29c96319facf",
   "af9d67bad068a77d165e145368e98bf7bd7cce72",
   "afac807436c5bf90861ae46294d25b7c9360f60c",
@@ -269,6 +273,7 @@
   "c7e94ec76ffd49121206a40048a36157440394f4",
   "c8206c0450c6928614577899b92fa389365c423d",
   "ca3bfeaaf87938454a789c7d8d30a5771491c632",
+  "cafedc58ea65d0336d7de5b8066f5df291faa5d5",
   "cb7c4b1e0799c9a617cace6b4a756103b5884c2d",
   "cd02e0a094953077217e2e62f3557b36a365acff",
   "ce315c58316f5328949c39b7af9474969c044c5f",