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The shape of educational inequality

Christopher L. Quarles, Ceren Budak, Paul Resnick
2020 Science Advances  
Hundreds of thousands of students drop out of school each year in the United States, despite billions of dollars of funding and myriad educational reforms. Existing research tends to look at the effect of easily measurable student characteristics. However, a vast number of harder-to-measure student traits, skills, and resources affect educational success. We present a conceptual framework for the cumulative effect of all factors, which we call student capital. We develop a method for estimating
more » ... student capital in groups of students and find that student capital is distributed exponentially in each of 140 cohorts of community college students. Students' ability to be successful does not behave like standard tests of intelligence. Instead, it acts like a limited resource, distributed unequally. The results suggest that rather than removing barriers related to easily measured characteristics, interventions should be focused on building up the skills and resources needed to be successful in school.
doi:10.1126/sciadv.aaz5954 pmid:32743067 pmcid:PMC7363455 fatcat:5weaqes2evg5xg2qzolt5kajli

GeoScope

Ceren Budak, Theodore Georgiou, Divyakant Agrawal, Amr El Abbadi
2013 Proceedings of the VLDB Endowment  
The First Law of Geography states "Everything is related to everything else, but near things are more related than distant things". This spatial significance has implications in various applications, trend detection being one of them. In this paper we propose a new algorithmic tool, GeoScope, to detect geo-trends. GeoScope is a data streams solution that detects correlations between topics and locations in a sliding window, in addition to analyzing topics and locations independently. GeoScope
more » ... fers theoretical guarantees for detecting all trending correlated pairs while requiring only sublinear space and running time. We perform various human validation tasks to demonstrate the value of GeoScope. The results show that human judges prefer GeoScope to the best performing baseline solution 4:1 in terms of the geographical significance of the presented information. As the Twitter analysis demonstrates, Geo-Scope successfully filters out topics without geo-intent and detects various local interests such as emergency events, political demonstrations or cultural events. Experiments on Twitter show that Geo-Scope has perfect recall and near-perfect precision.
doi:10.14778/2732240.2732242 fatcat:wn7biu6frzf4dcsvuxiyjpu3pu

Political Discussion is Abundant in Non-political Subreddits (and Less Toxic) [article]

Ashwin Rajadesingan, Ceren Budak, Paul Resnick
2021 arXiv   pre-print
Such qualification tasks are shown to improve crowdsourcing label quality (Budak, Goel, and Rao 2016) . The inter-rater agreement score as computed by Krippendorff's alpha was 0.55.  ...  We used a list of 277 political subreddits provided by (Rajadesingan, Resnick, and Budak 2020) and updated the list to include more recently created subreddits supporting Democratic primary candidates  ... 
arXiv:2104.09560v1 fatcat:e7vhonskjfc3jmvqe4734tkz7i

Solving path problems on the GPU

Aydın Buluç, John R. Gilbert, Ceren Budak
2010 Parallel Computing  
We consider the computation of shortest paths on Graphic Processing Units (GPUs). The blocked recursive elimination strategy we use is applicable to a class of algorithms (such as all-pairs shortest-paths, transitive closure, and LU decomposition without pivoting) having similar data access patterns. Using the all-pairs shortest-paths problem as an example, we uncover potential gains over this class of algorithms. The impressive computational power and memory bandwidth of the GPU make it an
more » ... active platform to run such computationally intensive algorithms. Although improvements over CPU implementations have previously been achieved for those algorithms in terms of raw speed, the utilization of the underlying computational resources was quite low. We implemented a recursively partioned all-pairs shortest-paths algorithm that harnesses the power of GPUs better than existing implementations. The alternate schedule of path computations allowed us to cast almost all operations into matrix-matrix multiplications on a semiring. Since matrix-matrix multiplication is highly optimized and has a high ratio of computation to communication, our implementation does not suffer from the premature saturation of bandwidth resources as iterative algorithms do. By increasing temporal locality, our implementation runs more than two orders of magnitude faster on an NVIDIA 8800 GPU than on an Opteron. Our work provides evidence that programmers should rethink algorithms instead of directly porting them to GPU.
doi:10.1016/j.parco.2009.12.002 fatcat:gpdffk6s4fa4tifrawtmq5x22a

Where the blogs tip

Ceren Budak, Divyakant Agrawal, Amr El Abbadi
2010 Proceedings of the First Workshop on Social Media Analytics - SOMA '10  
Why is it that some ideas or products become unusually successful and get adopted widely while others don't? This question has been puzzling many social scientists, economists, politicians and educators for a long time. Knowing the answer to this question can help deliberately start such successful cascades. Many theories have been introduced in this topic by economists and social scientists and these theories have been backed by small numbers of case studies. In this paper, we will focus on
more » ... popular theories introduced in "The Tipping Point" by Malcolm Gladwell. The basic idea is the crucial effect of three types of "fascinating" people that the author calls mavens, connectors and salesmen on the effectiveness of a cascade. Those people are claimed to "play a critical role in the word-of-mouth epidemics that dictate our tastes, trends and fashions". In this work, we investigate existence of mavens, connectors and salesmen in the blogosphere. We formally define what it means to be a maven, connector or a salesman and study their possible effect on the success of cascades in the blogosphere. We also study a fourth type of interesting actor that we call translator, an actor that acts as a bridge between different interest groups and communities. We observe that these four types of important players do in fact exist in the blogosphere and they have high correlation with successful cascades. More interestingly, we show that the cascades where these actors act as intermediaries rather than initiators are more likely to reach a larger size.
doi:10.1145/1964858.1964873 dblp:conf/kdd/BudakAA10 fatcat:7nuvx6rskzapbohceqoxuztwqe

Fair and Balanced? Quantifying Media Bias Through Crowdsourced Content Analysis

Ceren Budak, Sharad Goel, Justin M. Rao
2014 Social Science Research Network  
Word Count: 6,464 * Budak (cbudak@microsoft.com) is the corresponding author. We thank Seth Flaxman, Matthew Salganik, and Sid Suri for comments.  ... 
doi:10.2139/ssrn.2526461 fatcat:aaakwlxfszdqvf5iv4727yt2ki

On participation in group chats on Twitter

Ceren Budak, Rakesh Agrawal
2013 Proceedings of the 22nd international conference on World Wide Web - WWW '13  
The success of a group depends on continued participation of its members through time. We study the factors that affect continued user participation in the context of educational Twitter chats. To predict whether a user that attended her first session in a particular Twitter chat group will return to the group, we build 5F Model that captures five different factors: individual initiative, group characteristics, perceived receptivity, linguistic affinity, and geographical proximity. Through
more » ... stical data analysis of thirty Twitter chats over a two year period as well as a survey study, our work provides many insights about group dynamics in Twitter chats. We show similarities between Twitter chats and traditional groups such as the importance of social inclusion and linguistic similarity while also identifying important distinctions such as the insignificance of geographical proximity. We also show that informational support is more important than emotional support in educational Twitter chats, but this does not reduce the sense of community as suggested in earlier studies.
doi:10.1145/2488388.2488404 dblp:conf/www/BudakA13 fatcat:nbdiemzsrrcabenhbecevmz6du

Structural trend analysis for online social networks

Ceren Budak, Divyakant Agrawal, Amr El Abbadi
2011 Proceedings of the VLDB Endowment  
The identification of popular and important topics discussed in social networks is crucial for a better understanding of societal concerns. It is also useful for users to stay on top of trends without having to sift through vast amounts of shared information. Trend detection methods introduced so far have not used the network topology and has thus not been able to distinguish viral topics from topics that are diffused mostly through the news media. To address this gap, we propose two novel
more » ... tural trend definitions we call coordinated and uncoordinated trends that use friendship information to identify topics that are discussed among clustered and distributed users respectively. Our analyses and experiments show that structural trends are significantly different from traditional trends and provide new insights into the way people share information online. We also propose a sampling technique for structural trend detection and prove that the solution yields in a gain in efficiency and is within an acceptable error bound. Experiments performed on a Twitter data set of 41.7 million nodes and 417 million posts show that even with a sampling rate of 0.005, the average precision is 0.93 for coordinated trends and 1 for uncoordinated trends.
doi:10.14778/2021017.2021022 fatcat:glh3e7w5enbcfncayzb73y7s24

Keyword expansion techniques for mining social movement data on social media

Lia Bozarth, Ceren Budak
2022 EPJ Data Science  
AbstractPolitical and social scientists have been relying extensively on keywords such as hashtags to mine social movement data from social media sites, particularly Twitter. Yet, prior work demonstrates that unrepresentative keyword sets can lead to flawed research conclusions. Numerous keyword expansion methods have been proposed to increase the comprehensiveness of keywords, but systematic evaluations of these methods have been lacking. Our paper fills this gap. We evaluate five diverse
more » ... rd expansion techniques (or pipelines) on five representative social movements across two distinct activity levels. Our results guide researchers who aim to use social media keyword searches to mine data. For instance, we show that word embedding-based methods significantly outperform other even more complex and newer approaches when movements are in normal activity periods. These methods are also less computationally intensive. More importantly, we also observe that no single pipeline can identify little more than half of all movement-related tweets when these movements are at their peak mobilization period offline. However, coverage can increase significantly when more than one pipeline is used. This is true even when the pipelines are selected at random.
doi:10.1140/epjds/s13688-022-00343-9 fatcat:t57ounqsrzbkfopctukeumb4se

Dissecting the Spirit of Gezi: Influence vs. Selection in the Occupy Gezi Movement

Ceren Budak, Duncan Watts
2015 Sociological Science  
Do social movements actively shape the opinions and attitudes of participants by bringing together diverse groups that subsequently influence one another? Ethnographic studies of the 2013 Gezi uprising seem to answer "yes, " pointing to solidarity among groups that were traditionally indifferent, or even hostile, to one another. We argue that two mechanisms with differing implications may generate this observed outcome: "influence" (change in attitude caused by interacting with other
more » ... s); and "selection" (individuals who participated in the movement were generally more supportive of other groups beforehand). We tease out the relative importance of these mechanisms by constructing a panel of over 30,000 Twitter users and analyzing their support for the main Turkish opposition parties before, during, and after the movement. We find that although individuals changed in significant ways, becoming in general more supportive of the other opposition parties, those who participated in the movement were also significantly more supportive of the other parties all along. These findings suggest that both mechanisms were important, but that selection dominated. In addition to our substantive findings, our paper also makes a methodological contribution that we believe could be useful to studies of social movements and mass opinion change more generally. In contrast with traditional panel studies, which must be designed and implemented prior to the event of interest, our method relies on ex post panel construction, and hence can be used to study unanticipated or otherwise inaccessible events. We conclude that despite the well known limitations of social media, their "always on" nature and their widespread availability offer an important source of public opinion data.
doi:10.15195/v2.a18 fatcat:6yr7li7wqvefzctqwsjvxxjynu

Fair and Balanced? Quantifying Media Bias through Crowdsourced Content Analysis

Ceren Budak, Sharad Goel, Justin M. Rao
2016 Public Opinion Quarterly  
Word Count: 6,464 * Budak (cbudak@microsoft.com) is the corresponding author. We thank Seth Flaxman, Matthew Salganik, and Sid Suri for comments.  ... 
doi:10.1093/poq/nfw007 fatcat:zaobuwygj5blzovd2o4u5ncjau

Shocking the Crowd: The Effect of Censorship Shocks on Chinese Wikipedia

Ark Fangzhou Zhang, Danielle Livneh, Ceren Budak, Lionel P. Robert Jr., Daniel M. Romero
2017 arXiv   pre-print
Collaborative crowdsourcing has become a popular approach to organizing work across the globe. Being global also means being vulnerable to shocks -- unforeseen events that disrupt crowds -- that originate from any country. In this study, we examine changes in collaborative behavior of editors of Chinese Wikipedia that arise due to the 2005 government censor- ship in mainland China. Using the exogenous variation in the fraction of editors blocked across different articles due to the censorship,
more » ... e examine the impact of reduction in group size, which we denote as the shock level, on three collaborative behavior measures: volume of activity, centralization, and conflict. We find that activity and conflict drop on articles that face a shock, whereas centralization increases. The impact of a shock on activity increases with shock level, whereas the impact on centralization and conflict is higher for moderate shock levels than for very small or very high shock levels. These findings provide support for threat rigidity theory -- originally introduced in the organizational theory literature -- in the context of large-scale collaborative crowds.
arXiv:1704.00412v1 fatcat:cz7v3zotavbmnitnjvqmiuoyli

Do-Not-Track and the Economics of Third-Party Advertising

Ceren Budak, Sharad Goel, Justin M. Rao, Georgios Zervas
2014 Social Science Research Network  
Retailers regularly target users with online ads based on their web browsing activity, benefiting both the retailers, who can better reach potential customers, and content providers, who can increase ad revenue by displaying more e↵ective ads. The e↵ectiveness of such ads relies on third-party brokers that maintain detailed user information, prompting privacy legislation such as "do-not-track" that would limit or ban the practice. We gauge the economic costs of such privacy policies by
more » ... the anonymized web browsing histories of 14 million individuals. We find that 3% of retail sessions are currently initiated by ads capable of incorporating third-party information. Turning to content providers, we find that one-third of tra c is supported by third-party capable advertising, and the rate is particularly high (91%) for online news sites. Finally, we show that for many of the most popular content providers, modest subscription fees of $1-3 per month charged to loyal site users would be su cient to replace ad revenue. We conclude that do-not-track legislation would impact, but not fundamentally fracture, the Internet economy.
doi:10.2139/ssrn.2505643 fatcat:utcie72kwndfxanhqhlpvufjnu

Neural embeddings of scholarly periodicals reveal complex disciplinary organizations

Hao Peng, Qing Ke, Ceren Budak, Daniel M Romero, Yong-Yeol Ahn
2021 Science Advances  
Understanding the structure of knowledge domains is one of the foundational challenges in the science of science. Here, we propose a neural embedding technique that leverages the information contained in the citation network to obtain continuous vector representations of scientific periodicals. We demonstrate that our periodical embeddings encode nuanced relationships between periodicals and the complex disciplinary and interdisciplinary structure of science, allowing us to make
more » ... ry analogies between periodicals. Furthermore, we show that the embeddings capture meaningful "axes" that encompass knowledge domains, such as an axis from "soft" to "hard" sciences or from "social" to "biological" sciences, which allow us to quantitatively ground periodicals on a given dimension. By offering novel quantification in the science of science, our framework may, in turn, facilitate the study of how knowledge is created and organized.
doi:10.1126/sciadv.abb9004 pmid:33893092 pmcid:PMC8064639 fatcat:ajkliydplfe6fpthcldlrwyk2i

Dissecting the Spirit of Gezi: Influence vs. Selection in the Occupy Gezi Movement

Ceren Budak, Duncan J. Watts
2015 Social Science Research Network  
Do social movements actively shape the opinions and attitudes of participants by bringing together diverse groups that subsequently influence one another? Ethnographic studies of the 2013 Gezi uprising seem to answer "yes, " pointing to solidarity among groups that were traditionally indifferent, or even hostile, to one another. We argue that two mechanisms with differing implications may generate this observed outcome: "influence" (change in attitude caused by interacting with other
more » ... s); and "selection" (individuals who participated in the movement were generally more supportive of other groups beforehand). We tease out the relative importance of these mechanisms by constructing a panel of over 30,000 Twitter users and analyzing their support for the main Turkish opposition parties before, during, and after the movement. We find that although individuals changed in significant ways, becoming in general more supportive of the other opposition parties, those who participated in the movement were also significantly more supportive of the other parties all along. These findings suggest that both mechanisms were important, but that selection dominated. In addition to our substantive findings, our paper also makes a methodological contribution that we believe could be useful to studies of social movements and mass opinion change more generally. In contrast with traditional panel studies, which must be designed and implemented prior to the event of interest, our method relies on ex post panel construction, and hence can be used to study unanticipated or otherwise inaccessible events. We conclude that despite the well known limitations of social media, their "always on" nature and their widespread availability offer an important source of public opinion data.
doi:10.2139/ssrn.2610055 fatcat:ubyxgcvjcrdzha57v7t4oopel4
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