We gratefully acknowledge support from
the Simons Foundation
and member institutions

Computers and Society

New submissions

[ total of 7 entries: 1-7 ]
[ showing up to 2000 entries per page: fewer | more ]

New submissions for Tue, 25 Apr 17

[1]  arXiv:1704.06802 [pdf]
Title: Bike Renting Data Analysis: The Case of Dublin City
Comments: GISRUK 2017
Subjects: Computers and Society (cs.CY)

Public bike renting is more and more popular in cities to incentivise a reduction in car journeys and to boost the use of green transportation alternatives. One of the challenges of this application is to effectively plan the resources usage. This paper presents some analysis of Dublin bike renting scheme based on statistics and data mining. It provides available bike patterns at the most interesting bike stations, that is, the busiest and the quietest stations. Consistency checking with new data reinforces confidence in the patterns obtained. Identifying available bike patterns helps to better address user needs such as organising the rebalancing of the bike numbers between stations in advance of demand.

[2]  arXiv:1704.06903 [pdf]
Title: Moral Foundations of Political Discourse: Comparative Analysis of the Speech Records of the US Congress and the Japanese Diet
Comments: Originally submitted to the 3rd International Conference on Computational Social Science (IC2S2), July 10-13, 2017; 4 pages
Subjects: Computers and Society (cs.CY)

There has been a growing body of study on the relationship between public/political discourse and its moral-emotional foundations. Most of the studies, however, have been confined to a single country's context, lacking cross-cultural perspectives. Taking a comparative perspective, we examined the emotional and moral structures of political and public discussion observed in the U.S. and Japan by employing extensive text data that cover these two countries. Specifically, we conducted dictionary-based sentiment and moral analyses of floor debate in the U.S. Congress and the Japanese Diet over a long period of time. The analyses revealed intriguing cross-national patterns in the moral-emotional framework employed in parliamentary deliberations, which cast doubt on some of the dominant arguments in the field, including, among others, J. Haidt's moral foundation hypothesis.

[3]  arXiv:1704.07185 [pdf, other]
Title: FilteredWeb: A Framework for the Automated Search-Based Discovery of Blocked URLs
Comments: To appear in "Network Traffic Measurement and Analysis Conference 2017" (TMA2017)
Subjects: Computers and Society (cs.CY)

Various methods have been proposed for creating and maintaining lists of potentially filtered URLs to allow for measurement of ongoing internet censorship around the world. Whilst testing a known resource for evidence of filtering can be relatively simple, given appropriate vantage points, discovering previously unknown filtered web resources remains an open challenge.
We present a new framework for automating the process of discovering filtered resources through the use of adaptive queries to well-known search engines. Our system applies information retrieval algorithms to isolate characteristic linguistic patterns in known filtered web pages; these are then used as the basis for web search queries. The results of these queries are then checked for evidence of filtering, and newly discovered filtered resources are fed back into the system to detect further filtered content.
Our implementation of this framework, applied to China as a case study, shows that this approach is demonstrably effective at detecting significant numbers of previously unknown filtered web pages, making a significant contribution to the ongoing detection of internet filtering as it develops.
Our tool is currently deployed and has been used to discover 1355 domains that are poisoned within China as of Feb 2017 - 30 times more than are contained in the most widely-used public filter list. Of these, 759 are outside of the Alexa Top 1000 domains list, demonstrating the capability of this framework to find more obscure filtered content. Further, our initial analysis of filtered URLs, and the search terms that were used to discover them, gives further insight into the nature of the content currently being blocked in China.

Cross-lists for Tue, 25 Apr 17

[4]  arXiv:1704.06840 (cross-list from cs.DS) [pdf, ps, other]
Title: Ranking with Fairness Constraints
Subjects: Data Structures and Algorithms (cs.DS); Computers and Society (cs.CY); Information Retrieval (cs.IR)

The problem of ranking a set of items is fundamental in today's data-driven world. Ranking algorithms lie at the core of applications such as search engines, news feeds, and recommendation systems. However, recent events have pointed to the fact that algorithmic bias in rankings, which results in decreased fairness or diversity in the type of content presented, can promote stereotypes and propagate injustices. Motivated by such applications, we initiate the study of the traditional ranking problem with additional fairness constraints. Given a collection of items along with 1) the value of placing an item at a particular position, 2) the collection of possibly non-disjoint attributes (e.g., gender, race) of each item and 3) a collection of fairness constraints that upper bound the number of items with each attribute that are allowed to appear in the top positions of the ranking, the goal is to output a ranking that maximizes value while respecting the constraints. This problem encapsulates various well-studied problems related to matching as special cases and turns out to be hard to approximate even with simple constraints.
Our main technical contributions are exact and approximation algorithms and hardness results that, together, come close to settling the approximability of the constrained ranking maximization problem. Technically, our main results rely on novel insights about the standard linear programming relaxation for the constrained matching problem when the objective function satisfies certain properties that appear in common ranking metrics such as DCG, Spearman's rho or Bradley-Terry, along with the structure of fairness constraints. Overall, our results contribute to the growing set of algorithms that can counter algorithmic bias, and the structural insights obtained may find use in other algorithmic contexts related to ranking problems.

[5]  arXiv:1704.06860 (cross-list from cs.DB) [pdf, ps, other]
Title: Location Privacy in Spatial Crowdsourcing
Subjects: Databases (cs.DB); Cryptography and Security (cs.CR); Computers and Society (cs.CY); Human-Computer Interaction (cs.HC)

Spatial crowdsourcing (SC) is a new platform that engages individuals in collecting and analyzing environmental, social and other spatiotemporal information. With SC, requesters outsource their spatiotemporal tasks to a set of workers, who will perform the tasks by physically traveling to the tasks' locations. This chapter identifies privacy threats toward both workers and requesters during the two main phases of spatial crowdsourcing, tasking and reporting. Tasking is the process of identifying which tasks should be assigned to which workers. This process is handled by a spatial crowdsourcing server (SC-server). The latter phase is reporting, in which workers travel to the tasks' locations, complete the tasks and upload their reports to the SC-server. The challenge is to enable effective and efficient tasking as well as reporting in SC without disclosing the actual locations of workers (at least until they agree to perform a task) and the tasks themselves (at least to workers who are not assigned to those tasks). This chapter aims to provide an overview of the state-of-the-art in protecting users' location privacy in spatial crowdsourcing. We provide a comparative study of a diverse set of solutions in terms of task publishing modes (push vs. pull), problem focuses (tasking and reporting), threats (server, requester and worker), and underlying technical approaches (from pseudonymity, cloaking, and perturbation to exchange-based and encryption-based techniques). The strengths and drawbacks of the techniques are highlighted, leading to a discussion of open problems and future work.

Replacements for Tue, 25 Apr 17

[6]  arXiv:1606.09610 (replaced) [pdf, other]
Title: A Crowdsourcing Approach To Collecting Tutorial Videos -- Toward Personalized Learning-at-Scale
Subjects: Human-Computer Interaction (cs.HC); Computers and Society (cs.CY)
[7]  arXiv:1703.04993 (replaced) [pdf, other]
Title: On the Unhappiness of Software Developers
Comments: 10 pages, 1 figure. Accepted for presentation at the 21st International Conference on Evaluation and Assessment in Software Engineering (EASE'17)
Subjects: Software Engineering (cs.SE); Computers and Society (cs.CY)
[ total of 7 entries: 1-7 ]
[ showing up to 2000 entries per page: fewer | more ]

Disable MathJax (What is MathJax?)