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Hifza AfzalComputer Science,Balochistan University of information technology, engineering, and managementsciences, Quetta, Pakistan. Quetta, [email protected] Abstract—Social media is increasingly broadening up its horizons by making possibledifferent ways of communication between individual and groups. These differentways make us possible to understand one’s views, behavior, reactions, andactivities. Communication on Facebook is the common way to exchange thedifferent views. BUITEMS university students show their reactions on differentpublic Facebook pages through likes. The first classical signal ‘Like’ is thecommon feedback expression on Facebook.

The main objective of this paper is toevaluate the reactions of different type of users on different posts. Secondly,the impact of likes on a different type of posts. This has been done throughtaking different measures on the dataset fetched from Facepager tool. The paperfindings reveal that Facebook ‘like’ reaction can be very helpful forunderstanding students and their interests as well, in finding the moderate andweak correlation and regression measures between a type of posts and likes.Keywords— Social computing, social media, Post likes analysis, Facebook                                                                                                                                                  I.

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     IntroductionDuringthe past years, social media has played a highly influential role ininfluencing public opinion globally. This includes, for example, expressingtheir satisfaction, happiness, anger, and disapproval textually or visually1. Facebook has millions of active user groups sharing different viewsglobally about different topics 2. A large amount of social feedbackexpressed by social signals (e.g. like +1, rating) are assigned to webresources. ‘Like’ is the most common classical signal used to express reactiontowards posts social signal.

Conducting analysis on users’ likes in order todetermine their views through understanding their reactions towards differentposts.                                                                                                                                       II.    Proposed approachBUITEMS University,having several pages with majority students following and participating in it.Understanding their views regarding different issues is of core importance.Finding meanings from their reactions on public participation will be done andthen classifying them distinctively on bases of their likes on different posts.This will help to understand students’ different perspectives and activities bydeciphering meanings from their likes. This would be done through followingsteps: 1.

Capturing and storing public data from socialmedia (Facebook).2.Classifying individuals based on socialmedia behavior.3.Analyzing social media users’ likes, such astheir level of            reactions.4.

Predicting future activities based on socialmedia data.5.Understanding public perceptions and views. Identify applicable sponsor/s here. If no sponsors, delete this text box (sponsors).  Thispaper has been organized in following order: Section III is based on componentdetails of our thesis.

Section IV provides a complete methodology about the analysisperformed on Facebook likes. Section V shows the concluded results based on ouranalysis. In Section VI some predictable future works are estimated. SectionVII concludes this paper based on our analysis.                                                                                                                                                   III.   componentsThe dataset of 75 posts and its likes are obtained and isused then in Rstudio for further analysis. Results have been obtained in theform of charts, graphs, and tables.A.

    Dataset collection toolFacepager is a dataset obtaining tool for social media publicpages. For analysis of likes Facepager (Version 3.7) has been used, to collectFacebook posts and there likes.

B.    DatasetThe dataset used for analysis of Facebook post likes arefetched from BUITEMS University public Facebook page (BUITEMS Social Corner).The page current posts and its likes are obtained from Facepager tool throughselecting maximum pages option consisting of 75 posts. The dataset is exported in.

csv file, further used in Rstudio.C.    RstudioAn open-source free IDE used in this paper for statisticalcomputing on obtained dataset to perform several analyses resulting in severalanswers obtained in the form of charts and graphs.D.   Post typesFor performing analysis, posts have been categorized into twoforms, that are video posts and without video or other posts as this will makeus easy to understand and evaluate the interests of students towards these twodifferent categories of posts. Through this analysis, we will find the effectof number of likes on these two different types of posts.

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