Browsing by Subject "Social networking (online)"
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Item Open Access A content-based social network study of evliyâ çelebi's seyahatnâme-bitlis section(Springer, London, 2012) Karbeyaz, Ceyhun; Can, Ethem F; Can, Fazlı; Kalpaklı, MehmetEvliyâ Çelebi, an Ottoman writer, scholar and world traveler, visited most of the territories and also some of the neighboring countries of the Ottoman Empire in the seventeenth century. He took notes about his trips and wrote a 10-volume book called Seyahatnâme (Book of Travels). In this paper, we present two methods for constructing social networks by using textual data and apply it to Seyahatnâme-Bitlis Section from book IV. The first social network construction method is based on proximity of co-occurence of names. The second method is based on 2-pair associations obtained by association rule mining by using sliding text blocks as transactions. The social networks obtained by these two methods are validated using a Monte Carlo approach by comparing them with the social network created by a scholar-historian. © 2012 Springer-Verlag London Limited.Item Open Access Cryptographic solutions for genomic privacy(Springer, 2016-02) Ayday, ErmanWith the help of rapidly developing technology, DNA sequencing is becoming less expensive. As a consequence, the research in genomics has gained speed in paving the way to personalized (genomic) medicine, and geneticists need large collections of human genomes to further increase this speed. Furthermore, individuals are using their genomes to learn about their (genetic) predispositions to diseases, their ancestries, and even their (genetic) compatibilities with potential partners. This trend has also caused the launch of health-related websites and online social networks (OSNs), in which individuals share their genomic data (e.g., OpenSNP or 23andMe). On the other hand, genomic data carries much sensitive information about its owner. By analyzing the DNA of an individual, it is now possible to learn about his disease predispositions (e.g., for Alzheimer’s or Parkinson’s), ancestries, and physical attributes. The threat to genomic privacy is magnified by the fact that a person’s genome is correlated to his family members’ genomes, thus leading to interdependent privacy risks. In this work, focusing on our existing and ongoing work on genomic privacy, we will first highlight one serious threat for genomic privacy. Then, we will present the high level descriptions of our cryptographic solutions to protect the privacy of genomic data. © International Financial Cryptography Association 2016.Item Open Access Do computer games enhance learning about conflicts? A cross-national inquiry into proximate and distant scenarios in Global Conflicts(Pergamon Press, 2015) Kampf, R.; Cuhadar E.Interactive conflict resolution and peace education have developed as two major lines of practice to tackle intractable inter-group conflicts. Recently, new media technologies such as social media, computer games, and online dialogue are added to the existing set of tools used for peace education. However, a debate is emerging as to how effective they are in motivating learning and teaching skills required for peace building. We take issue with this question and have conducted a study investigating the effect of different conflict contexts on student learning. We have designed a cross-national experimental study with Israeli-Jewish, Palestinian, and Guatemalan undergraduate students using the Israeli-Palestinian and Guatemalan scenarios in the computer game called "Global Conflicts." The learning effects of these scenarios were systematically analyzed using pre- and post-test questionnaires. The study indicated that Israeli-Jews and Palestinians acquired more knowledge from the Guatemalan game than Guatemalans acquired from the Israeli-Palestinian game. All participants acquired knowledge about proximate conflicts after playing games about these scenarios, and there were insignificant differences between the three national groups. Israeli-Jews and Palestinians playing the Israeli-Palestinian game changed their attitudes about this conflict, while Guatemalans playing the Guatemalan game did not change their attitudes about this case. All participants changed their attitudes about distant conflicts after playing games about these scenarios. © 2014 Elsevier Ltd.Item Open Access Facebook communities about nostalgic photos of Turkey: creative practices of remembering and representing the past(Routledge, 2017) Savaş, Ö.This article focuses on Facebook communities about nostalgic photos of Turkey to explore how citizenship is enacted through the participatory and collaborative use of social media to remember and represent the past. By sharing their personal photos, knowledge, testimonies, narratives and life stories, members of these communities actively and creatively use social media to generate new ways of remembering and representing the past, as well as improving its accessibility and visibility. Furthermore, through exchanging affectively and politically charged photos and conversations about the past, participants fashion nostalgia as a public feeling that becomes a source for affective political criticism of the present. This article addresses the participatory and collaborative creation of knowledge and memory of the past to discuss everyday creative citizenship practices facilitated by social media. © 2017 Informa UK Limited, trading as Taylor & Francis Group.Item Open Access Location recommendations for new businesses using check-in data(IEEE, 2016-12) Eravci, Bahaeddin; Bulut, Neslihan; Etemoğlu, C.; Ferhatosmanoğlu, HakanLocation based social networks (LBSN) and mobile applications generate data useful for location oriented business decisions. Companies can get insights about mobility patterns of potential customers and their daily habits on shopping, dining, etc.To enhance customer satisfaction and increase profitability. We introduce a new problem of identifying neighborhoods with a potential of success in a line of business. After partitioning the city into neighborhoods, based on geographical and social distances, we use the similarities of the neighborhoods to identify specific neighborhoods as candidates for investment for a new business opportunity. We present two solutions for this new problem: i) a probabilistic approach based on Bayesian inference for location selection along with a voting based approximation, and ii) an adaptation of collaborative filtering using the similarity of neighborhoods based on co-existence of related venues and check-in patterns. We use Foursquare user check-in and venue location data to evaluate the performance of the proposed approach. Our experiments show promising results for identifying new opportunities and supporting business decisions using increasingly available check-in data sets. © 2016 IEEE.Item Open Access Microalgae immobilized by nanofibrous web for removal of reactive dyes from wastewater(American Chemical Society, 2015) Keskin, N. O. S.; Celebioglu A.; Uyar, Tamer; Tekinay, T.In this study, we have developed microalgae immobilized by polysulfone nanofibrous web (microalgae/PSU-NFW) for the removal of reactive dyes (Remazol Black 5 (RB5) and Reactive Blue 221 (RB221). Here, an electrospinning technique was used to produce polysulfone nanofibrous web (PSU-NFW) as a free-standing material on which microalgae Chlamydomona reinhardtii was immobilized on PSU-NFW. The decolorization capacities of microalgae/PSU-NFW were significantly higher than that of pristine PSU-NFW. The decolorization rate for RB5 was calculated as 72.97 ± 0.3% for microalgae/PSU-NFW, whereas it was 12.36 ± 0.3% for the pristine PSU-NFW. In the case of RB221 solution, decolorization rates were achieved as 30.2 ± 0.23 and 5.51 ± 0.4% for microalgae/PSU-NFW and pristine PSU-NFW, respectively. Reusability tests revealed that microalgae/PSU-NFW can be used in at least three successive decolorization steps in which the decolorization rate of the RB5 was found to be 51 ± 0.69% after the third reuse step. These results are promising and therefore suggest that microalgae/PSU-NFW could be applicable for the decolorization of dyes because of their versatility and reusability.Item Open Access More network conscious than ever? Challenges, strategies, and analytic labor of users in the facebook environment(Wiley-Blackwell Publishing, Inc., 2013) Karakayali, N.; Kilic A.As is widely observed, social network sites (SNS) constitute a new environment of interaction where users encounter various challenges that they usually do not encounter in other environments. This study aims to provide an in-depth understanding of how users deal with the challenges in this unique environment, paying particular attention to the ways in which they examine and reflect on their social ties and networks. On the basis of 36 semistructured interviews with Facebook users, the article presents the hypothesis that participants of SNS develop a tendency to become highly observant and inquisitive about their networks and are frequently involved in an activity that the authors call analytic labor. © 2013 International Communication Association.Item Open Access Multi-resolution social network community identification and maintenance on big data platform(IEEE, 2013-06-07) Aksu, Hidayet; Canım, M.; Chang, Y.-C.; Körpeoğlu, İbrahim; Ulusoy, ÖzgürCommunity identification in social networks is of great interest and with dynamic changes to its graph representation and content, the incremental maintenance of community poses significant challenges in computation. Moreover, the intensity of community engagement can be distinguished at multiple levels, resulting in a multi-resolution community representation that has to be maintained over time. In this paper, we first formalize this problem using the k-core metric projected at multiple k values, so that multiple community resolutions are represented with multiple k-core graphs. We then present distributed algorithms to construct and maintain a multi-k-core graph, implemented on the scalable big-data platform Apache HBase. Our experimental evaluation results demonstrate orders of magnitude speedup by maintaining multi-k-core incrementally over complete reconstruction. Our algorithms thus enable practitioners to create and maintain communities at multiple resolutions on different topics in rich social network content simultaneously. © 2013 IEEE.Item Open Access An Online Causal Inference Framework for Modeling and Designing Systems Involving User Preferences: A State-Space Approach(Hindawi Limited, 2017) Delibalta, I.; Baruh, L.; Kozat, S. S.We provide a causal inference framework to model the effects of machine learning algorithms on user preferences. We then use this mathematical model to prove that the overall system can be tuned to alter those preferences in a desired manner. A user can be an online shopper or a social media user, exposed to digital interventions produced by machine learning algorithms. A user preference can be anything from inclination towards a product to a political party affiliation. Our framework uses a state-space model to represent user preferences as latent system parameters which can only be observed indirectly via online user actions such as a purchase activity or social media status updates, shares, blogs, or tweets. Based on these observations, machine learning algorithms produce digital interventions such as targeted advertisements or tweets. We model the effects of these interventions through a causal feedback loop, which alters the corresponding preferences of the user. We then introduce algorithms in order to estimate and later tune the user preferences to a particular desired form. We demonstrate the effectiveness of our algorithms through experiments in different scenarios. © 2017 Ibrahim Delibalta et al.Item Open Access Online Contextual Influence Maximization in social networks(Institute of Electrical and Electronics Engineers Inc., 2017) Sarıtaç, Ömer; Karakurt, Altuğ; Tekin, CemIn this paper, we propose the Online Contextual Influence Maximization Problem (OCIMP). In OCIMP, the learner faces a series of epochs in each of which a different influence campaign is run to promote a certain product in a given social network. In each epoch, the learner first distributes a limited number of free-samples of the product among a set of seed nodes in the social network. Then, the influence spread process takes place over the network, other users get influenced and purchase the product. The goal of the learner is to maximize the expected total number of influenced users over all epochs. We depart from the prior work in two aspects: (i) the learner does not know how the influence spreads over the network, i.e., it is unaware of the influence probabilities; (ii) influence probabilities depend on the context. We develop a learning algorithm for OCIMP, called Contextual Online INfluence maximization (COIN). COIN can use any approximation algorithm that solves the offline influence maximization problem as a subroutine to obtain the set of seed nodes in each epoch. When the influence probabilities are Hölder continuous functions of the context, we prove that COIN achieves sublinear regret with respect to an approximation oracle that knows the influence probabilities for all contexts. Moreover, our regret bound holds for any sequence of contexts. We also test the performance of COIN on several social networks, and show that it performs better than other methods. © 2016 IEEE.Item Open Access Privacy and security in the genomic era(ACM, 2016-10) Ayday, Erman; Hubaux, Jean-PierreWith the help of rapidly developing technology, DNA sequencing is becoming less expensive. As a consequence, the research in genomics has gained speed in paving the way to personalized (genomic) medicine, and geneticists need large collections of human genomes to further increase this speed. Furthermore, individuals are using their genomes to learn about their (genetic) predispositions to diseases, their ancestries, and even their (genetic) compatibilities with potential partners. This trend has also caused the launch of health-related websites and online social networks (OSNs), in which individuals share their genomic data (e.g., Open-SNP or 23 and Me). On the other hand, genomic data carries much sensitive information about its owner. By analyzing the DNA of an individual, it is now possible to learn about his disease predispositions (e.g., for Alzheimer's or Parkinson's), ancestries, and physical attributes. The threat to genomic privacy is magnified by the fact that a person's genome is correlated to his family members' genomes, thus leading to interdependent privacy risks. This short tutorial will help computer scientists better understand the privacy and security challenges in today's genomic era. We will first highlight the significance of genomic data and the threats for genomic privacy. Then, we will present the high level descriptions of the proposed solutions to protect the privacy of genomic data and we will discuss future research directions. No prerequisite knowledge on biology or genomics is required for the attendees of this proposal. We only require the attendees to have a slight background on cryptography and statistics.Item Open Access S3-TM: scalable streaming short text matching(Association for Computing Machinery, 2015) Basık F.; Gedik, B.; Ferhatosmanoğlu, H.; Kalender, M. E.Micro-blogging services have become major venues for information creation, as well as channels of information dissemination. Accordingly, monitoring them for relevant information is a critical capability. This is typically achieved by registering content-based subscriptions with the micro-blogging service. Such subscriptions are long-running queries that are evaluated against the stream of posts. Given the popularity and scale of micro-blogging services like Twitter and Weibo, building a scalable infrastructure to evaluate these subscriptions is a challenge. To address this challenge, we present the S3-TM system for streaming short text matching. S3-TM is organized as a stream processing application, in the form of a data parallel flow graph designed to be run on a data center environment. It takes advantage of the structure of the publications (posts) and subscriptions to perform the matching in a scalable manner, without broadcasting publications or subscriptions to all of the matcher instances. The basic design of S$$^3$$3-TM uses a scoped multicast for publications and scoped anycast for subscriptions. To further improve throughput, we introduce publication routing algorithms that aim at minimizing the scope of the multicasts. First set of algorithms we develop are based on partitioning the word co-occurrence frequency graph, with the aim of routing posts that include commonly co-occurring words to a small set of matchers. While effective, these algorithms fell short in balancing the load. To address this, we develop the SALB algorithm, which provides better load balance by modeling the load more accurately using the word-to-post bipartite graph. We also develop a subscription placement algorithm, called LASP, to group together similar subscriptions, in order to minimize the subscription matching cost. Furthermore, to achieve good scalability for increasing number of nodes, we introduce techniques to handle workload skew. Finally, we introduce load shedding techniques for handling unexpected load spikes with small impact on the accuracy. Our experimental results show that S3-TM is scalable. Furthermore, the SALB algorithm provides more than 2.5× throughput compared to the baseline multicast and outperforms the graph partitioning-based approaches.