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Study of Social Networks : modeling and Analysis

Abstract : Currently social networks focus on the sharing and exchange of opinions, videos, photos, music,news and others informations, one of its objectives is to establish direct and indirect linkswith users. Social networks also promote products, people (their political or artistic image) orinfluential brands.Social networks are changing rapidly, so we’re looking to see the evolution of these sharingtools, and see how social networks change over time.We have the opportunity to study the events that occur in social networks thanks to the amount ofdata they produce. In the current market there are tools that allow the analysis of social networks,but most tools are not free, and 100% free tools disappear over time. For this reason we decidedto produce computer tools able to extract and analyse the data of the social networks studied.This study begins with the state of the art, where we describe the context of the problem, thework that led to this study and a summary of the contributions made during the thesis that wepresent briefly in the rest of the abstract.i. First we focus on the geo-linguistic fingerprint and language evolution in Twitter. Accessto content of messages sent by a group of subscribers of a social network may be usedto identify and quantify some features of a group. The feature can represent the level ofinterest in an event or product, or the popularity of an idea, or of a musical hit, or of apolitical figure. The feature can also represent how language is used and transformed,how words are written and how new grammatical rules appear.ii. Then we study the evolution of the cultural phenomenon called meme in social networks.Memes were defined by R. Dowkins as a cultural phenomenon that spreads through nongeneticforms. We examine three of the most popular memes of the internet and examinetheir impact on society in the Mediterranean countries. We use for analysing Google Trends, Topsy (a tool to measure the popularity of words on Twitter) and YouTube toquantify the impact of memes in the Mediterranean society.iii. After that we study the YouTube recommendation graph based on measurements andstochastic tools. We confirm that recommendation lists influence the views of a video.We focus on the recommendation system that boosts the popularity of videos. We buildfirst a graph that captures the recommendation system in YouTube and we study the relationshipbetween the number of views of a video and the average number of views of avideo in its recommendation list.iv. To conclude we describe the online tools available and the tools that we developed duringthe thesis. The online tools Topsy, Trendistic and Google Trends allowed us to analyseplatforms like YouTube and Twitter. We also produced tools based on API’s: in Twitterwe used the Streaming function to download and analyse tweets, with the Topsy APIwe studied the evolution of the language and the use of words, and the YouTube’s APIsallowed us to describe the behaviour on the lists of recommendations and the popularityof videos.
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Submitted on : Wednesday, July 1, 2020 - 11:12:12 AM
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  • HAL Id : tel-02886062, version 1



Yonathan Portilla. Study of Social Networks : modeling and Analysis. Social and Information Networks [cs.SI]. Université d'Avignon, 2019. English. ⟨NNT : 2019AVIG0235⟩. ⟨tel-02886062⟩



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