Relevant bibliographies by topics / FACEBOOK GRAPH

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'FACEBOOK GRAPH'

Author: Grafiati
Published: 11 September 2023

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Journal articles on the topic "FACEBOOK GRAPH"

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Weaver, Jesse, and Paul Tarjan. "Facebook Linked Data via the Graph API." Semantic Web 4, no. 3 (2013): 245–50. http://dx.doi.org/10.3233/sw-2012-0078.

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Alsaif, Suleiman Ali, Adel Hidri, and Minyar Sassi Hidri. "Towards Inferring Influential Facebook Users." Computers 10, no. 5 (May 9, 2021): 62. http://dx.doi.org/10.3390/computers10050062.

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Because of the complexity of the actors and the relationships between them, social networks are always represented by graphs. This structure makes it possible to analyze the effectiveness of the network for the social actors who are there. This work presents a social network analysis approach that focused on processing Facebook pages and users who react to posts to infer influential people. In our study, we are particularly interested in studying the relationships between the posts of the page, and the reactions of fans (users) towards these posts. The topics covered include data crawling, graph modeling, and exploratory analysis using statistical tools and machine learning algorithms. We seek to detect influential people in the sense that the influence of a Facebook user lies in their ability to transmit and disseminate information. Once determined, these users have an impact on business for a specific brand. The proposed exploratory analysis has shown that the network structure and its properties have important implications for the outcome of interest.
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Procaci, Thiago Baesso, Sean Wolfgand M. Siqueira, and Leila Cristina Vasconcelos de Andrade. "Finding Experts on Facebook Communities." International Journal of Knowledge Society Research 5, no. 2 (April 2014): 7–19. http://dx.doi.org/10.4018/ijksr.2014040102.

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Online communities have become important places for users to share information. In this context, the work described in this article aims to analyze computational methods that could allow us to identify users with the highest expertise levels on a specific knowledge domain in an online community. In this study the authots extracted data from a Java discussion group from an online community - Facebook, captured some important information and represented the community as a graph. Then, the authors compared the Bow-tie structure of this community with the ones from the Web and from a forum that are described in the literature. In addition, the authors tested some graph metrics and algorithms in order to analyze if they could provide a method to find the experts in this online community. The results show that four of the tested metrics can indicate if a user is an expert or not.
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Xu, Jin, Yu Zhong, and Bo Peng. "Parallel k-Way Partitioning Approach for Large Graphs." Advanced Materials Research 912-914 (April 2014): 1309–12. http://dx.doi.org/10.4028/www.scientific.net/amr.912-914.1309.

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With the emergence of large social networks, such as Facebook and Twitter, graphs with millions to billions vertices are common. Instead of processing the network within a single machine, all the applications related are intended to be done in a distributed way using a cluster of commodity machines. In this paper, we study the parallel graph partitioning problem, which is the fundamental operation for large graphs. With the help of Hadoop/MapReduce, we propose aparallel k-way partitioningapproach. Unlike the previous ones, which require enough memory to keep the whole graph data within, our novel approach breaks such limitations. Also, due to the distributed nature, it is easy to integrate our partitioning approach into existed parallel platforms. We conduct extensive experiments on real graphs and synthetic graphs. All the experimental results prove the effectiveness and efficiency of our approach.
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Banerjee, Arijeet, and Pijush Kanti Kumar. "Review of Shortest Path Algorithm." International Journal of Computer Science and Mobile Computing 11, no. 4 (April 30, 2022): 1–8. http://dx.doi.org/10.47760/ijcsmc.2022.v11i04.001.

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Shortest path algorithm. Graphs are an example of non-linear data structure. A graph is a collection of nodes which are connected by edges. The definition of graph G = (V, E) is basically a collection of vertices and edges. Graphs can be classified on the basis of types of edges. Directed graphs have each of the edges directed which means the edges connecting the two nodes defines the way it is connected from and to. On the other side, undirected graphs have edges which have no direction. The edges of a graph have weights which are associated with it. The weight of an edge can be thought as the cost of the edge. Let’s assume there are two vertices representing two cities, then the weight of the edge between the vertices may represent the distance between the cities. Given a given graph and a particular node, we can find a path of least total weight from that node to other vertices of the graph. The total weight of the path will be the sum of the weights of the edges. Graphs can be used in real life to find the shortest path between two destinations, used in social networking sites like facebook and the world wide web where the web pages are represented by the nodes. Dijkstra’s Algorithm, Floyd – Warshall, Bellman Ford Algorithm, Johnson’s algorithm, A* search algorithm are some of the shortest path algorithms.
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Das, Sauvik, and Adam Kramer. "Self-Censorship on Facebook." Proceedings of the International AAAI Conference on Web and Social Media 7, no. 1 (August 3, 2021): 120–27. http://dx.doi.org/10.1609/icwsm.v7i1.14412.

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We report results from an exploratory analysis examining “last-minute” self-censorship, or content that is filtered after being written, on Facebook. We collected data from 3.9 million users over 17 days and associate self-censorship behavior with features describing users, their social graph, and the interactions between them. Our results indicate that 71% of users exhibited some level of last-minute self-censorship in the time period, and provide specific evidence supporting the theory that a user’s “perceived audience” lies at the heart of the issue: posts are censored more frequently than comments, with status updates and posts directed at groups censored most frequently of all sharing use cases investigated. Furthermore, we find that: people with more boundaries to regulate censor more; males censor more posts than females and censor even more posts with mostly male friends than do females, but censor no more comments than females; people who exercise more control over their audience censor more content; and, users with more politically and age diverse friends censor less, in general.
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Zhang, Yilin, Marie Poux-Berthe, Chris Wells, Karolina Koc-Michalska, and Karl Rohe. "Discovering political topics in Facebook discussion threads with graph contextualization." Annals of Applied Statistics 12, no. 2 (June 2018): 1096–123. http://dx.doi.org/10.1214/18-aoas1191.

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Terrana, Diego, Agnese Augello, and Giovanni Pilato. "Analysis of Facebook Users' Relationships Through Sentiment Classification: A Case Study of Italian Politicians." International Journal of Semantic Computing 08, no. 03 (September 2014): 301–17. http://dx.doi.org/10.1142/s1793351x14400108.

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We illustrate a system that analyzes the homepage of a Facebook user or group in order to automatically detect who has discussed what and how it has been discussed. We have focused the analysis on three main actors of Italian politics. The goal is to find people who agree or disagree about given topics with the owner of the Facebook page under analysis. All public posts shared by a user are retrieved by an ad hoc built crawler. Information such as 'posts', 'comments', 'likes', are extracted from the Facebook page. Each post is classified as belonging to a set of predefined categories and its sentiment is also detected as being positive, negative or neutral. All the comments to that post are therefore analyzed and categorized together with its sentiment polarity. For each Facebook user under analysis a statistics of the topics dealt with is made, and for each category a graph is created where the concordance of sentiment is highlighted between the posts belonging to a given class and the related comments of the people interacting with the user or group under analysis. The graph can therefore be used to profile the user relationships according to sentiment classification.
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Nugroho, Arif, and Anna Agustina. "Examining Corporate Engagement in Social Media: Advancing The Use of Facebook for Corporation Page." CoverAge: Journal of Strategic Communication 10, no. 2 (March 29, 2020): 1–10. http://dx.doi.org/10.35814/coverage.v10i2.1377.

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This article focuses on the engagement conducted through Facebook fan page. Analyzing responses of customer to the postings made by corporate user will give input on what need to be put in attention and revise to meet the need of customers. The need to put more attention on details of social media feature becomes essentials in advancing engagement through –in this case- Facebook. The aim of the study is to identify highest engagement items in Facebook feature by examining Telkomsel Facebook page postings as a case. The data is content in Telkomsel Facebook. Data collection used Facebook-graph data mining technique. Media content analysis method conducted to analyze all the data using engagement concept. The study found 7 items that have the highest engagement rate on Facebook, which are: visual indicator in the form of video (1), 200 characters on Facebook texts (2), information with corporate brand, Telkomsel, on it (3); entertainment content (4), a call to action message to engage fans, such as quiz (5); high engagement happened in weekdays (6), to the multiple postings (7), and posting hours is in peak hours (8.00 – 17.00).
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Wu, Kuixian, Jian Gao, Rong Chen, and Xianji Cui. "Vertex Selection Heuristics in Branch-and-Bound Algorithms for the Maximum k-Plex Problem." International Journal on Artificial Intelligence Tools 28, no. 05 (August 2019): 1950015. http://dx.doi.org/10.1142/s0218213019500155.

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As a relaxation of clique in graph theory, k-plex is a powerful tool for analyzing social networks and identifying cohesive structures in graphs. Recently, more and more researchers have concentrated on the algorithms for the maximum k-plex problem. Among those algorithms, a branch-and-bound algorithm proposed very recently shows a good performance on solving large sparse graphs, but does not work well on social networks. In this paper, we propose two novel vertex selection heuristic strategies for branching. The first one employs historical information of vertex reduction, and the second one is a combination of the first heuristic and the degree-based approach. Intensive experiments on Facebook benchmark show that the algorithm combining our heuristics outperforms the state-of-the-art algorithms.
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Dissertations / Theses on the topic "FACEBOOK GRAPH"

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Iu, Marco. "Serviceklass för Facebook Graph API." Thesis, Linnéuniversitetet, Institutionen för datavetenskap, fysik och matematik, DFM, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-13729.

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Rapporten grundar sig på en delmängd av ett projekt som utfördes åt uppdragsgivaren SocialWorks. Projektet innefattade bland annat att arbeta mot externa webbtjänster. Genom webbtjänster kan webbaserade datorprogram kommunicera och skicka data till varandra. Då en webbtjänst nyttjas behöver utvecklaren sätta sig in i API:et för webbtjänsten. Denna rapport tar upp ett antal problem som kan uppstå vid användandet av en sådan webbtjänst och hur dessa problem kan lösas genom att skapa ett mellanlager i form av en serviceklass. Alla API-anrop ska gå genom serviceklassen och därmed behöver kodförändringar endast göras i serviceklassen ifall API:et förändras. Som ett resultat av arbetet togs en serviceklass fram som underlättar användningen av Facebooks Graph API tillsammans med PHP-ramverket Zend Framework. Genom serviceklassen behöver användaren inte sätta sig in i Facebook Graph API i detalj. Dessutom skapades en testapplikation i Zend dels för att testa serviceklassens funktionalitet och dels för att hantera så kallade testanvändare som Facebooks Graph API tillhandahåller.
This report is based on a subset of a project that was made for the company SocialWorks. The project included working with web services. Through web services, web applications are able to communicate and send data to each other. When a web service is used, the user has to study the web service API. This report addresses a number of problems that might arise from the use of such web services and how these problems can be solved by creating a service class that is used as a middle layer. All API calls will be made through the service class and thus changes in the API will only require modification of code in the service class. As a result of this report a service class was created using the PHP framework Zend Framework to facilitate the use of Facebook's Graph API. By using the service class, the user does not have to study the Facebook Graph API in detail. A test application was created to test the service class functionality and manage test users provided by the Facebook Graph API.
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Enchill, Happy S. "LDConnect - a SoLiD compliant interface for the Facebook social graph." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/105985.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 31-32).
LDConnect is a service that allows Crosscloud applications to easily interact with Facebook data. This paper describes the design of LDConnect and the benefits that it provides Crosscloud developers over other methods of interacting with Facebook data. LDConnect's live translation of JSON data to RDF and vice-a-versa makes it easy for developers to run CRUD applications on Facebook elements using the same access methods they would use to access Crosscloud backends.
by Happy S. Enchill.
M. Eng.
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Pereira, Jorge André Henriques. "Leveraging facebook’s open graph to develop an environmental persuasive application." Master's thesis, Faculdade de Ciências e Tecnologia, 2013. http://hdl.handle.net/10362/10998.

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
Social networking sites persuade millions of users each day to adopt specific behaviors. Using the persuasive principles inherent to these sites to increase environmental awareness and reduce our ecological footprint can be challenging but certainly worthy. The DEAP project has already invested time and resources to address persuasion through different devices for a broad audience. However, there are still many obstacles when it comes to such a delicate subject as people’s routines. For many years, social factors have prevented people from adopting a way of living friendlier to our Environment. Whether it is due to lack of proper knowledge about this topic or simply because they are not willing to change, the truth is that we are eventually reaching a point where it will be too late to keep our planet as we know it. Consequently, the time has arrived when there is great need for a platform to bring existing efforts together no matter where they come from but the goal they share: change incorrect behaviors towards environmental sustainability. Towards this ambitious goal a board game was developed and integrated in Facebook capable of merging third-party applications and an important and valuable basis for future research in the field of persuasion.
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Coco, Giuseppe Antonio. "Social media evaluation for non-profit organizations : The case of Oxfam Italia." Thesis, Uppsala universitet, Medier och kommunikation, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-232708.

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The thesis presents an evaluation of the Facebook page of the Italian non-profit organization Oxfam Italia from November 2013 to March 2014. The research’s aim is to analyze the community which follows the organization, how this community interacts with it and how the moderators of the page communicate with its followers. The research aims also to find ways to increase Oxfam Italia’s performance on Facebook. The theoretical framework focuses on non-profit marketing and its peculiarities, Social Media Marketing and notions such as engagement and brand community. The methods used in the research consist in data mining and content analysis. Data have been gathered from Facebook Insights and through the issuing of FQL queries from the Facebook Graph API. The research found out that Oxfam has more female followers than male (62% vs 36,5%), the age range of them is 25-44 years. Oxfam’s presence, in particular, is very rooted in the region of Tuscany (where its headquarter is). Facebook followers showed a very good attitude toward the organization, even though criticisms are common, and Oxfam used its social media presence mainly to update the followers concerning ongoing activities and to urge to on-line activism. The users’ favourite engagement method was “liking” photographic contents.
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Jiránek, Aleš. "Analýza a vizualizace vztahů nad daty ze sociálních sítí." Master's thesis, Vysoká škola ekonomická v Praze, 2015. http://www.nusl.cz/ntk/nusl-203987.

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This diploma thesis deals with various types of relations observable in social networks. First part contains survey of existing papers focused on social media data analysis and visualisations. This survey is followed by research of existing visualisation applications. The contribution of this thesis is a new look at relations on social networks, from the side of relationship between users who write posts on any given topic. To visualize these relations was chosen network graph. On the basis of established criteria existing instruments were evaluated and since any of them did not meet all requirements, I created new application for visualising relations. Thesis also includes a description of selection the appropriate libraries for its implementation, explanation of user interface and a summary of configuration options and customization. The end of the work contains analysis and visualisations made with newly-created tool.
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Hrdlička, Pavel. "Model rozhraní sociální sítě elektronického obchodu." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2011. http://www.nusl.cz/ntk/nusl-222931.

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The diploma thesis analyzes modern social networks, with focus on Facebook network in Czech environment. It shows Facebook tools and its possible usage for marketing purposes. Facebook functionality is shown on practical examples, including own Facebook application. It contains suggestions for Facebook marketing strategy improvements.
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Novosad, Andrej. "Využití metod dolování dat pro analýzu sociálních sítí." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2013. http://www.nusl.cz/ntk/nusl-236424.

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Thesis discusses data mining the social media. It gives an introduction about the topic of data mining and possible mining methods. Thesis also explores social media and social networks, what are they able to offer and what problems do they bring. Three different APIs of three social networking sites are examined with their opportunities they provide for data mining. Techniques of text mining and document classification are explored. An implementation of a web application that mines data from social site Twitter using the algorithm SVM is being described. Implemented application is classifying tweets based on their text where classes represent tweets' continents of origin. Several experiments executed both in RapidMiner software and in implemented web application are then proposed and their results examined.
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Sáez-Trumper, Diego. "Finding relevant people in online social networks." Doctoral thesis, Universitat Pompeu Fabra, 2013. http://hdl.handle.net/10803/283658.

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The objective of this thesis is to develop novel techniques to find relevant people in Online Social Networks (OSN). To that end, we consider different notions of relevance, taking the point of view of the OSN providers (like Facebook) and advertisers, as well as considering the people who are trying to push new ideas and topics on the network. We go beyond people's popularity, showing that the users with a lot of followers are not necessarily the most relevant. Specifically, we develop three algorithms that allow to: (i) compute the monetary value that each user produces for OSN provider; (ii) find users that push new ideas and create trends; and (iii) a recommender system that allows advertisers (focusing in local shops, like restaurants or pubs) to find potential customers. Furthermore, we also provide useful insights about users' behavior according to their relevance and popularity, showing - among other things - that most active users are usually more relevant than the popular ones. Moreover, we show that usually very popular users arrive late to the new trends, and that there are less popular, but very active users that generate value and push new ideas in the network.
L'objectiu d'aquesta tesi és desenvolupar noves tècniques per trobar persones rellevants en les Xarxes Socials a Internet. Així doncs, considerem diferents nocions de rellevància, tenint en compte el punt de vista dels prove ïdors del servei (com Facebook) i dels anunciants, però també de persones que intenten proposar noves idees i temes a la xarxa. La nostra investigació va més enllà de la popularitat de les persones, mostra que els usuaris amb molts seguidors no són necessàriament els més rellevants. Específicament, desenvolupem tres algorismes que permeten: (i) calcular el valor (monetari) que cada usuari produeix per al prove ïdor del servei; (ii) trobar usuaris que proposen noves idees i creen tendències; i (iii) un sistema de recomanació que permet als anunciants (centrant-nos en botigues locals, com ara un restaurant o un pub) trobar clients potencials. Addicionalment, lliurem informació útil sobre el comportament dels usuaris segons la seva rellevància i popularitat, mostrant, entre altres coses, que els usuaris més actius solen ser més rellevants que els populars. A més a més, mostrem que normalment els usuaris molt populars arriben tard a les noves tendències, mentre que usuaris de menor popularitat, però molt actius, generen valor i fomenten noves idees a la xarxa .
El objetivo de esta tesis es desarrollar nuevas técnicas para encontrar personas relevantes en las Redes Sociales en Internet. Para ello, consideramos diferentes nociones de relevancia, tomando el punto de vista de los proveedores del servicio (como Facebook) y de los anunciantes, pero también de las personas que intentan proponer nuevas ideas y temas en la red. Nuestra investigación va más allá de la popularidad de las personas, mostrando que los usuarios con muchos seguidores no son necesariamente los más relevantes. Espeficamente, desarollamos tres algoritmos que permiten: (i) calcular el valor (monetario) que cada usuario produce para el proveedor del servicio; (ii) encontrar usuarios que proponen nuevas ideas y crean tendencias; y (iii) un sistema de recomendación que permite a los anunciantes (centrándonos en tiendas locales, tales como un restaurant o un pub) encontrar potenciales clientes. Adicionalmente, proporcionamos información útil sobre el comportamiento de los usuarios según su relevancia y popularidad, mostrando - entre otras cosas - que los usuarios más activos suelen ser más relevantes que los populares. Más aún, mostramos que normalmente los usuarios muy populares llegan tarde a las nuevas tendencias, y que existen usuarios menos populares, pero muy activos que generan valor y fomentan nuevas ideas en la red.
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BERHE, ZENAWI HAILESLASSIE. "SENTIMENT ANALYSIS IN SOCIAL MEDIA ON FACEBOOK." Thesis, 2019. http://dspace.dtu.ac.in:8080/jspui/handle/repository/16695.

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In ithis iadvanced istage itechnology iwhere igiving i& idevouring imanagements ithrough ionline itrade ihas iturned iinto iday ito iday iactivities i(task), ieverybody iwants ito itake ian iinterest iand igive isuppositions iabout ithe iadministrations ihe/she ispends. ithese idays iare ioccurring isubstantially imore ion isocial iareas ias iopposed ito iin ia ifeedback ibox. iFacebook iis ia istandout iamongst ithe imost iregularly iutilized ionline inetworking iareas iwhere iindividuals ivoice itheir isentiments ion iattractive imuch ieverything. isuch ia isignificant inumber iof ispecialist iorganizations itake ithe istage ito iadvance itheir iadministrations iamong ithe iclients. iMedia itransmission isection iis ione iof ithem. iIt iis ivery ievident ithat inumerous iTelecommunication iorganization ikeeps iup ia iFacebook ipage ior igathering ito iraise itheir imanagements ito ithe iclients iand iget idisapproval ifrom ithem. iLimitless iis ibeing idelivered ialong ithese ilines ievery iday. In ithis ithesis, iwe iwill iseparate ievery ione iof ithe isentiments i(remarks ias icontent iinformation) ifrom ieach iindividual iprofile ipages iutilizing iFacebook igraph iAPI iis igiven iby iFacebook iapplication i& iexperience icommotion iscrubbing, iapplying isentiment i& iclassifier ifor icomputing iopinion iextremity igo ito ichoice iwhether ioffers iare igiven iby iorganization iis ireceiving igreat iinput ior inot. iAnd iin ithis ithesis ifor iour isentiment ianalysis iI iused inaïve iBayes iclassifier itechniques.
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Abdelkamel, Abdelmadjid. "Facebook et les dispositifs de traçabilité vus sous l’angle du droit canadien." Thèse, 2013. http://hdl.handle.net/1866/10010.

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Aujourd’hui, on parle du Web social. Facebook par exemple, porte bien la marque de son époque ; il est devenu le réseau social le plus convoité dans le monde. Toutefois, l’entreprise a été souvent critiquée en raison de sa politique qui porte atteinte à la vie privée des personnes. Par le truchement de ses modules sociaux, Facebook a le potentiel de collecter et d’utiliser des informations considérables sur les internautes à leur insu et sans leur consentement. Ce fait est malheureusement méconnu de la majorité d’entre eux. Certes, l’entreprise doit vivre économiquement et l’exploitation des renseignements personnels constitue pour elle une source de revenu. Toutefois, cette quête de subsistance ne doit pas se faire au détriment de la vie privée des gens. En dépit des outils juridiques dont le Canada dispose en matière de protection de la vie privée, des entreprises du Web à l’image de Facebook réussissent à les contourner.
Today we talk about the social Web. Facebook for example bears the mark of its time, as it becomes the most coveted social networking Web site in the world. However, the company has been criticized due to its policy that violates people's privacy. Through its social plugins, Facebook has the potential to collect considerable amounts of information about users without their knowledge and without their consent, a fact which is unknown to most of them. Certainly, the company must ensure its economic stability through these activities. However, this quest for subsistence should not be to the detriment of people's privacy. Canada has legal tools for the protection of privacy that allow users to deal with this kind of threat. However, Web companies such Facebook succeed to circumvent the law.
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Books on the topic "FACEBOOK GRAPH"

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I, Prince Far. Facebook Graph API development with Flash: Beginner's guide : build social Flash applications fully integrated with the Facebook Graph API. Birmingham, U.K: Packt Pub., 2010.

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Apeksha, Singh, ed. Facebook application development with Graph API cookbook: Over 90 recipes to create your own exciting Facebook applications at an incredibly fast pace with Facebook Graph API. Birmingham, U.K: Packt Publishing, 2011.

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Dunbar, Robin I. M., Marco Conti, Valerio Arnaboldi, and Andrea Passarella. Online Social Networks: Human Cognitive Constraints in Facebook and Twitter Personal Graphs. Elsevier Science & Technology Books, 2015.

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Dunbar, Robin I. M., Marco Conti, Valerio Arnaboldi, and Andrea Passarella. Online Social Networks: Human Cognitive Constraints in Facebook and Twitter Personal Graphs. Elsevier, 2015.

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Book chapters on the topic "FACEBOOK GRAPH"

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Raj P. M., Krishna, Ankith Mohan, and K. G. Srinivasa. "Graph Structure of Facebook." In Computer Communications and Networks, 87–100. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-96746-2_5.

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Dannen, Chris, and Christopher White. "What the Social Graph Can Do for Your App." In Beginning iOS Apps with Facebook and Twitter APIs, 1–8. Berkeley, CA: Apress, 2011. http://dx.doi.org/10.1007/978-1-4302-3543-9_1.

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Griffel, Sandra. "Social Graphs – Neue Perspektiven durch Facebook Connect & Co. für Communities von Touristik Anbietern." In Social Web im Tourismus, 217–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12508-9_16.

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Lieber, Sven, Ben De Meester, Ruben Verborgh, and Anastasia Dimou. "EcoDaLo: Federating Advertisement Targeting with Linked Data." In Semantic Systems. In the Era of Knowledge Graphs, 87–103. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59833-4_6.

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Abstract A key source of revenue for the media and entertainment domain is ad targeting: serving advertisements to a select set of visitors based on various captured visitor traits. Compared to global media companies such as Google and Facebook that aggregate data from various sources (and the privacy concerns these aggregations bring), local companies only capture a small number of (high-quality) traits and retrieve an unbalanced small amount of revenue. To increase these local publishers’ competitive advantage, they need to join forces, whilst taking the visitors’ privacy concerns into account. The EcoDaLo consortium, located in Belgium and consisting of Adlogix, Pebble Media, and Roularta Media Group as founding partners, aims to combine local publishers’ data without requiring these partners to share this data across the consortium. Usage of Semantic Web technologies enables a decentralized approach where federated querying allows local companies to combine their captured visitor traits, and better target visitors, without aggregating all data. To increase potential uptake, technical complexity to join this consortium is kept minimal, and established technology is used where possible. This solution was showcased in Belgium which provided the participating partners valuable insights and suggests future research challenges. Perspectives are to enlarge the consortium and provide measurable impact in ad targeting to local publishers.
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"Facebook and the Social Graph: Who Benefits?" In Social Media 101, 155–56. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9781118256138.ch39.

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Akhtar, Nadeem, and Mohd Vasim Ahamad. "Graph Tools for Social Network Analysis." In Advances in Wireless Technologies and Telecommunication, 18–33. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2814-2.ch002.

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A social network can be defined as a complex graph, which is a collection of nodes connected via edges. Nodes represent individual actors or people in the network, whereas edges define relationships among those actors. Most popular social networks are Facebook, Twitter, and Google+. To analyze these social networks, one needs specialized tools for analysis. This chapter presents a comparative study of such tools based on the general graph aspects as well as the social network mining aspects. While considering the general graph aspects, this chapter presents a comparative study of four social network analysis tools—NetworkX, Gephi, Pajek, and IGraph—based on the platform, execution time, graph types, algorithm complexity, input file format, and graph features. On the basis of the social network mining aspects, the chapter provides a comparative study on five specialized tools—Weka, NetMiner 4, RapidMiner, KNIME, and R—with respect to the supported mining tasks, main functionality, acceptable input formats, output formats, and platform used.
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Akhtar, Nadeem, and Mohd Vasim Ahamad. "Graph Tools for Social Network Analysis." In Research Anthology on Digital Transformation, Organizational Change, and the Impact of Remote Work, 485–500. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-7297-9.ch025.

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A social network can be defined as a complex graph, which is a collection of nodes connected via edges. Nodes represent individual actors or people in the network, whereas edges define relationships among those actors. Most popular social networks are Facebook, Twitter, and Google+. To analyze these social networks, one needs specialized tools for analysis. This chapter presents a comparative study of such tools based on the general graph aspects as well as the social network mining aspects. While considering the general graph aspects, this chapter presents a comparative study of four social network analysis tools—NetworkX, Gephi, Pajek, and IGraph—based on the platform, execution time, graph types, algorithm complexity, input file format, and graph features. On the basis of the social network mining aspects, the chapter provides a comparative study on five specialized tools—Weka, NetMiner 4, RapidMiner, KNIME, and R—with respect to the supported mining tasks, main functionality, acceptable input formats, output formats, and platform used.
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Dey, Paramita, and Krishnendu Dutta. "Social Network Analysis of Different Parameters Derived From Real-Time Facebook Profiles." In Advances in Wireless Technologies and Telecommunication, 95–108. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2814-2.ch006.

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With the advent of online social media, it is possible to collect large information and extract information. One of the powerful roles that networks play is to bridge gap between the local and the global perspectives. For example, social network analysis could be used to offer explanations for how simple processes at the level of individual nodes and links can have a global effect. Social networks like Twitter, Facebook, LinkedIn are very large in size with millions of vertices and billions of edges. To collect meaningful information from these densely connected graphs and huge volume of data, it is important to find proper topology of the network as well as conduct analysis based on different network parameters. The main objective of this work is to study the network parameters commonly used to explain social structures. We extract data from the three real-time Facebook accounts using the Netvizz application, analyze and evaluate their network parameters on some widely recognized graph topology using Gephi, a free and open source software.
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Schick, Johannes, Martin Kuboschek, and Wolfram Manfred Lippe. "Context Specific Modeling of Communicational and Informational Content in Facebook." In Advances in Wireless Technologies and Telecommunication, 109–24. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2814-2.ch007.

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In this chapter, the authors apply context specific methods to formalize communicational parameters for different profile groups in a social network platform, taking Facebook as an example. Information is posted to or shared with distinct user groups. The context specific approach is used to describe informational content of exchanged data and to formalize privacy settings in a social graph. Communicational and informational parameters are specified with direction and communicational content in a context specific model. Relations are defined to model communicational and informational interactions as well as environmental factors taking influence on the profile groups. The textual representation of this approach is introduced to describe models in a text-based form.
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Bansal, Neetika, Vishal Goyal, and Simpel Rani. "Experimenting Language Identification for Sentiment Analysis of English Punjabi Code Mixed Social Media Text." In Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines, 1470–79. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-6303-1.ch076.

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People do not always use Unicode, rather, they mix multiple languages. The processing of codemixed data becomes challenging due to the linguistic complexities. The noisy text increases the complexities of language identification. The dataset used in this article contains Facebook and Twitter messages collected through Facebook graph API and twitter API. The annotated English Punjabi code mixed dataset has been trained using a pipeline Dictionary Vectorizer, N-gram approach with some features. Furthermore, classifiers used are Logistic Regression, Decision Tree Classifier and Gaussian Naïve Bayes are used to perform language identification at word level. The results show that Logistic Regression performs best with an accuracy of 86.63 with an F-1 measure of 0.88. The success of machine learning approaches depends on the quality of labeled corpora.
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Conference papers on the topic "FACEBOOK GRAPH"

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Ugander, Johan. "Scaling graph computations at facebook." In the 22nd International Conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2487788.2487982.

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Hong, Yunfeng, Yu-Cheng Lin, Chun-Ming Lai, S. Felix Wu, and George A. Barnett. "Profiling Facebook Public Page Graph." In 2018 International Conference on Computing, Networking and Communications (ICNC). IEEE, 2018. http://dx.doi.org/10.1109/iccnc.2018.8390301.

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Nayak, Deveeshree, Summer Prince, and Rosario Robinson. "Information privacy risk assessment of Facebook Graph Search." In 2014 Science and Information Conference (SAI). IEEE, 2014. http://dx.doi.org/10.1109/sai.2014.6918309.

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Ebadian, Soroush, and Xin Huang. "Fast Algorithm for K-Truss Discovery on Public-Private Graphs." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/313.

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In public-private graphs, users share one public graph and have their own private graphs. A private graph consists of personal private contacts that only can be visible to its owner, e.g., hidden friend lists on Facebook and secret following on Sina Weibo. However, existing public-private analytic algorithms have not yet investigated the dense subgraph discovery of k-truss, where each edge is contained in at least k-2 triangles. This paper aims at finding k-truss efficiently in public-private graphs. The core of our solution is a novel algorithm to update k-truss with node insertions. We develop a classification-based hybrid strategy of node insertions and edge insertions to incrementally compute k-truss in public-private graphs. Extensive experiments validate the superiority of our proposed algorithms against state-of-the-art methods on real-world datasets.
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Kirman, Ben, Shaun Lawson, and Conor Linehan. "Gaming On and Off the Social Graph: The Social Structure of Facebook Games." In 2009 International Conference on Computational Science and Engineering. IEEE, 2009. http://dx.doi.org/10.1109/cse.2009.266.

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Saelim, Kwanrutai, Taweewat Luangwiriya, and Rachada Kongkachandra. "Using Conceptual Graph to Represent Semantic Relation of Thai Facebook Posts in Marketing." In 2019 14th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP). IEEE, 2019. http://dx.doi.org/10.1109/isai-nlp48611.2019.9045702.

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Elghanuni, Ramzi Hamid, Rabab Alayham Abbas Helmi, and Muhammad Irsyad Abdullah. "Improved detection of Facebook anomalies and abnormalities using graph-based and machine learning techniques." In PROCEEDING OF THE 1ST INTERNATIONAL CONFERENCE ON ADVANCED RESEARCH IN PURE AND APPLIED SCIENCE (ICARPAS2021): Third Annual Conference of Al-Muthanna University/College of Science. AIP Publishing, 2022. http://dx.doi.org/10.1063/5.0094026.

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Klaysri, Thidawan. "Facebook Customer Engagement Graph Analysis Using K-core, M-core and Km-core Methods." In ICCDE 2021: 2021 7th International Conference on Computing and Data Engineering. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3456172.3456215.

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Helmi, Rabab Alayham Abbas, Ramzi Hamid Elghanuni, and Muhammad Irsyad Abdullah. "Effect the Graph Metric to Detect Anomalies and Non-Anomalies on Facebook Using Machine Learning Models." In 2021 IEEE 12th Control and System Graduate Research Colloquium (ICSGRC). IEEE, 2021. http://dx.doi.org/10.1109/icsgrc53186.2021.9515227.

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N. Zehmakan, Ahad, Charlotte Out, and Sajjad Hesamipour Khelejan. "Why Rumors Spread Fast in Social Networks, and How to Stop It." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/27.

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We study a rumor spreading model where individuals are connected via a network structure. Initially, only a small subset of the individuals are spreading a rumor. Each individual who is connected to a spreader, starts spreading the rumor with some probability as a function of their trust in the spreader, quantified by the Jaccard similarity index. Furthermore, the probability that a spreader diffuses the rumor decreases over time until they fully lose their interest and stop spreading. We focus on determining the graph parameters which govern the magnitude and pace that the rumor spreads in this model. We prove that for the rumor to spread to a sizable fraction of the individuals, the network needs to enjoy ``strong'' expansion properties and most nodes should be in ``well-connected'' communities. Both of these characteristics are, arguably, present in real-world social networks up to a certain degree, shedding light on the driving force behind the extremely fast spread of rumors in social networks. Furthermore, we formulate a large range of countermeasures to cease the spread of a rumor. We introduce four fundamental criteria which a countermeasure ideally should possess. We evaluate all the proposed countermeasures by conducting experiments on real-world social networks such as Facebook and Twitter. We conclude that our novel decentralized countermeasures (which are executed by the individuals) generally outperform the previously studied centralized ones (which need to be imposed by a third entity such as the government).
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