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TO ENGAGE STUDENT IN SOCIAL MEDIA NETWORK- Creating And Using Digital Games For Learning In Elementary And Secondary Education

The Use Of Digital Games In Education Has Gained Considerable Popularity In The Last Years Due To The Fact That These Games Are Considered To Be Excellent Tools For Teaching And Learning And Offer To Students An Engaging And Interesting Way Of Participating And Learning. In This Study, The Design And Implementation Of Educational Activities That Include Game Creation And Use In Elementary And Secondary Education Is Presented. The Proposed Educational Activities’ Content Covers The Parts Of The Curricula Of All The Informatics Courses, For Each Education Level Separately, That Include The Learning Of Programming Principles. The Educational Activities Were Implemented And Evaluated By Teachers Through A Discussion Session. The Findings Indicate That The Teachers Think That Learning Through Creating And Using Games Is More Interesting And That They Also Like The Idea Of Using Various Programming Environments To Create Games In Order To Teach Basic Programming Principles To Students.

DRIMUX Dynamic Rumor Influence Minimization With User Experience In Social Networks

With The Soaring Development Of Large Scale Online Social Networks, Online Information Sharing Is Becoming Ubiquitous Every Day. Various Information Is Propagating Through Online Social Networks Including Both The Positive And Negative. In This Paper, We Focus On The Negative Information Problems Such As The Online Rumors. With The Soaring Development Of Large Scale Online Social Networks, Online Information Sharing Is Becoming Ubiquitous Everyday. Various Information Is Propagating Through Online Social Networks Including Both The Positive And Negative. In This Paper, We Focus On The Negative Information Problems Such As The Online Rumors. Rumor Blocking Is A Serious Problem In Large-scale Social Networks. Malicious Rumors Could Cause Chaos In Society And Hence Need To Be Blocked As Soon As Possible After Being Detected. In This Paper, We Propose A Model Of Dynamic Rumor Influence Minimization With User Experience (DRIMUX). Our Goal Is To Minimize The Influence Of The Rumor (i.e., The Number Of Users That Have Accepted And Sent The Rumor) By Blocking A Certain Subset Of Nodes. A Dynamic Ising Propagation Model Considering Both The Global Popularity And Individual Attraction Of The Rumor Is Presented Based On A Realistic Scenario. In Addition, Different From Existing Problems Of Influence Minimization, We Take Into Account The Constraint Of User Experience Utility. Specifically, Each Node Is Assigned A Tolerance Time Threshold. If The Blocking Time Of Each User Exceeds That Threshold, The Utility Of The Network Will Decrease. Under This Constraint, We Then Formulate The Problem As A Network Inference Problem With Survival Theory, And Propose Solutions Based On Maximum Likelihood Principle. Experiments Are Implemented Based On Large-scale Real World Networks And Validate The Effectiveness Of Our Method.

USER PROFILE MATCHING- Privacy-Preserving User Profile Matching In Social Networks

In This Paper, We Consider A Scenario Where A User Queries A User Profile Database, Maintained By A Social Networking Service Provider, To Identify Users Whose Profiles Match The Profile Specified By The Querying User. A Typical Example Of This Application Is Online Dating. Most Recently, An Online Dating Website, Ashley Madison, Was Hacked, Which Resulted In A Disclosure Of A Large Number Of Dating User Profiles. This Data Breach Has Urged Researchers To Explore Practical Privacy Protection For User Profiles In A Social Network. In This Paper, We Propose A Privacy-preserving Solution For Profile Matching In Social Networks By Using Multiple Servers. Our Solution Is Built On Homomorphic Encryption And Allows A User To Find Out Matching Users With The Help Of Multiple Servers Without Revealing To Anyone The Query And The Queried User Profiles In Clear. Our Solution Achieves User Profile Privacy And User Query Privacy As Long As At Least One Of The Multiple Servers Is Honest. Our Experiments Demonstrate That Our Solution Is Practical.

PHARMACOVIGILANCE FROM SOCIAL MEDIA- Pharmacovigilance From Social Media An Improved Random Subspace Method For Identifying Adverse Drug Events

Social Media-based Pharmacovigilance Has Great Potential To Augment Current Efforts And Provide Regulatory Authorities With Valuable Decision Aids. Among Various Pharmacovigilance Activities, Identifying Adverse Drug Events (ADEs) Is Very Important For Patient Safety. However, In Health-related Discussion Forums, ADEs May Confound With Drug Indications And Beneficial Effects, Etc. Therefore, The Focus Of This Study Is To Develop A Strategy To Identify ADEs From Other Semantic Types, And Meanwhile To Determine The Drug That An ADE Is Associated With. And Then Get The Id Of An User Who Share The ADE On The Medical Social Media. The User Id Detect By Using Naïve Bayes Algorithm.