Introduction to Social Computing cs6301 Introduction to Social Computing Ding-Zhu Du University of Texas at Dallas First, I want to thank you for you presence. ********In this presentation I will try to introduce The social network which is a theoretical structure to study relationships between individuals, groups, organizations, or even entire societies.  It is related to a wide range of disciplines. These disciplines include, but are not limited to information science, biology, economics, geography, communication studies, and so on.. The study of social networks begins with the late eighteenth century, two sociologists (Émile [ei'mi:l] Durkheim and Ferdinand ['fɝdənænd] Fer迪南de Tönnies) foreshadowed the idea of social networks in their theories and research of social groups. Nowadays, we study social networks using network analysis to identify social communities, pick influential person, and design good software. lidong.wu@utdallas.edu

Abstract Computer network has been used to represent and to build up social relations, called social networks which forms a basis to study social science. Such study is a new research area in computer science, called social computing. This course will introduce theoretical foundation for social computing and fundamental results in theory of social computing.

Goal Let students learn techniques in design and analysis of approximation algorithms, especially those appearing in study of social computing. Lead students to frontier of research in social computing.

Computational Social Networks --computational data networks Weili Wu Ding-Zhu Du University of Texas at Dallas First, I want to thank you for you presence. ********In this presentation I will try to introduce The social network which is a theoretical structure to study relationships between individuals, groups, organizations, or even entire societies.  It is related to a wide range of disciplines. These disciplines include, but are not limited to information science, biology, economics, geography, communication studies, and so on.. The study of social networks begins with the late eighteenth century, two sociologists (Émile [ei'mi:l] Durkheim and Ferdinand ['fɝdənænd] Fer迪南de Tönnies) foreshadowed the idea of social networks in their theories and research of social groups. Nowadays, we study social networks using network analysis to identify social communities, pick influential person, and design good software. lidong.wu@utdallas.edu

Reference books

Theory of Social Computing --computational social networks Weili Wu Ding-Zhu Du University of Texas at Dallas First, I want to thank you for you presence. ********In this presentation I will try to introduce The social network which is a theoretical structure to study relationships between individuals, groups, organizations, or even entire societies.  It is related to a wide range of disciplines. These disciplines include, but are not limited to information science, biology, economics, geography, communication studies, and so on.. The study of social networks begins with the late eighteenth century, two sociologists (Émile [ei'mi:l] Durkheim and Ferdinand ['fɝdənænd] Fer迪南de Tönnies) foreshadowed the idea of social networks in their theories and research of social groups. Nowadays, we study social networks using network analysis to identify social communities, pick influential person, and design good software. lidong.wu@utdallas.edu

Abstract Computer network has been used to represent and to build up social relations, called social networks which forms a basis to study social science. Such study is a new research area in computer science, called social computing. This book will introduce theoretical foundation for social computing and show you fundamental results in theory of social computing.

Not “Prerequisites”

Optimal Social Influence Upcoming Springer Book: Optimal Social Influence Wen Xu, Weili Wu University of Texas at Dallas First, I want to thank you for you presence. ********In this presentation I will try to introduce The social network which is a theoretical structure to study relationships between individuals, groups, organizations, or even entire societies.  It is related to a wide range of disciplines. These disciplines include, but are not limited to information science, biology, economics, geography, communication studies, and so on.. The study of social networks begins with the late eighteenth century, two sociologists (Émile [ei'mi:l] Durkheim and Ferdinand ['fɝdənænd] Fer迪南de Tönnies) foreshadowed the idea of social networks in their theories and research of social groups. Nowadays, we study social networks using network analysis to identify social communities, pick influential person, and design good software. lidong.wu@utdallas.edu

What is a Social Network? Lecture 1-1 What is a Social Network? Ding-Zhu Du University of Texas at Dallas First, I want to thank you for you presence. ********In this presentation I will try to introduce The social network which is a theoretical structure to study relationships between individuals, groups, organizations, or even entire societies.  It is related to a wide range of disciplines. These disciplines include, but are not limited to information science, biology, economics, geography, communication studies, and so on.. The study of social networks begins with the late eighteenth century, two sociologists (Émile [ei'mi:l] Durkheim and Ferdinand ['fɝdənænd] Fer迪南de Tönnies) foreshadowed the idea of social networks in their theories and research of social groups. Nowadays, we study social networks using network analysis to identify social communities, pick influential person, and design good software. lidong.wu@utdallas.edu

Outline Social Network Online Social Networks Community Structure Rumor Blocking Power Law 1. Brief overview of social networks 2. How to build applications on top of the social network –  Think about a social network being MS Windows, We can build applications on it.

What is a Network? Web definition: A network consists of two or more nodes that are linked in order to share resources. A network contains a set of nodes, or points, connected by links. The nodes can share infor via links.

What is Social Network? Wikipedia Definition: Social Structure Nodes: Social actors (individuals or organizations) Links: Social relations a social structure made of social actors (individuals or organizations) called “nodes”, which are tied by one or more specific Social relations, such as friendship, kinship, religions, knowledge or prestige. The nodes or actors as part of network data would seem to be pretty straight-forward. Our study mainly focus on the relations among actors.

Example 1: Friendship Network Nodes: all persons in the world A link exists between two persons if they know each other.

Property of Friendship Six Degrees of Separation Milgram (1967) The experiment: Random people from Nebraska were to send a letter (via intermediaries) to a stock broker in Boston. Could only send to someone with whom they know. Six links were needed. In the network of people’s social relation, there is a theory, called Six Degree of Separation, that everyone and everything is six or fewer steps away. a brilliant psychologist, The goal was to measure the number of steps for the letters to reach the broker. Stanley Milgram (1933-1984)

Chinese Observation 八竿子打不着 形容二者之间关系疏远或毫无关联。“竿”也作“杆”。

Friend Family Friend Supervise Family Friend Lidong Wu Friend Roommate Here is an example. A chain of "a friend of a friend" statements can connect any two people in a maximum of six steps.

“The small world network is a type of mathematical graph in which most nodes are not neighbors of one another, but most nodes can be reached from every other by a small number of hops or steps.”

Example 2: Coauthorship Network Nodes: all publication authors A link exists between two authors if they are coauthors in a publication.

Coauthorship Network is a Small World Network Distribution in Dec.2010 Erdős number: is the collaboration distance with mathematician Paul Erdős. Erdös number  0  ---      1 person Erdös number  1  ---    504 people Erdös number  2  ---   6593 people Erdös number  3  ---  33605 people Erdös number  4  ---  83642 people Erdös number  5  ---  87760 people Erdös number  6  ---  40014 people Erdös number  7  ---  11591 people Erdös number  8  ---   3146 people Erdös number  9  ---    819 people Erdös number 10  ---    244 people Erdös number 11  ---     68 people Erdös number 12  ---     23 people Erdös number 13  ---      5 people * Two persons are linked if they are coauthors of an article. This is another example related to co-authorship network. Two persons are linked if they are coauthors of an article. The Erdős number is the number of steps is required for a person to reach Paul Erdős in this network. influential mathematician who spent a large portion of his later life living out of a suitcase, and writing papers with those of his colleagues willing to give him room and board What is your Erdős number?

My Erdős number is 3 because I am coauthors of two advisers Dr My Erdős number is 3 because I am coauthors of two advisers Dr. Wu and Dr. Du. They are coauthors of well known mathematicians, Professor Ronald Graham at UC San Diego and Prof. Kleitman at MIT who are coauthors of Erdős. My Erdős number is 2.

Example 3: Flight Map Is a Small World Network Nodes: all cities with an airport. A link exists between two cities if there exists a direct flight between them. Every two airports can be connected by a few flights even internationally. Searching cheap airline ticket can be formulated into a shortest path problem in a social network.

Search Cheap Ticket Find a cheap ticket between two given cities. It is a shortest path problem in a social network. Need to add connection information to network. There are about 28,537 commercial flights in the sky in the U.S. on any given day. Every two airports can be connected by a few flights even internationally. Searching cheap airline ticket can be formulated into a shortest path problem in a social network.

Network Construction AA123 AA456 Chicago Dallas AA789

Network Construction 8am 8am 9am 9am 1pm 1pm 3pm 3pm Dallas

Network construction 8am 8am 9am 9am 1pm 1pm 3pm 3pm Dallas

Outline Social Network Online Social Networks Community Structure Rumor Blocking Power Law 1. Brief overview of social networks 2. How to build applications on top of the social network –  Think about a social network being MS Windows, We can build applications on it.

Social Network is online in Internet Facebook: friendship linkedIn: friendship ResearchGate: coauthorship

Online Social Networks (OSN) Social influence occurs when one's emotions, opinions, or behaviors are affected by others. Although social influence is possible in the workplace, universities, communities, it is most popular online.

Internet provides a platform to record and to develop social networks help in creating Social Networks。

What Are OSN Used For? Activity of social network users. Content posted on social network: what do you do with your social networking profile? everything can be recorded

Usage Example Political Election for Mayor of London (2012) Candidates (left to right) ： Ken Livingstone, Boris Johnson and Brian Paddick. Kenneth Robert Livingstone (born 17 June 1945) is a British Labour Party politician,  the first elected Mayor of London from the creation of the office in 2000 until 2008, as Labour candidate in London's mayoral elections of 2008 and 2012, both times losing to Conservative candidate Boris Johnson. Alexander Boris de Pfeffel Johnson (born 19 June 1964) is a British Conservative Party politician, who has served as Mayor of London since 2008, Selected as Conservative candidate for the 2008 London mayoral election, Johnson defeated Labourincumbent Ken Livingstone to become Mayor. In 2012, he was re-elected as Mayor, again defeating Livingstone. Brian Paddick, a British politician, and was the Liberal Democrat candidate for the London mayoral election, 2008 and the London mayoral election, 2012. http://www.telegraph.co.uk/technology/news/9239077/Twitter-data-predicts-Boris-Johnson-victory.html

Prediction of Boris Johnson Victory

How to Predict? Analysis posts on Facebook and Twitter: “Sentiment Analysis” . Find 7% more positive sentiment towards Mr. Johnson than Mr. Livingstone. Predict 54% of the vote for Mr. Johnson. Google Insights, tracking web trends, Almost five times more searches for “Boris Johnson” than for “Ken Livingstone” via google.co.uk. Of the total number of web searches for both candidates, 60% were for “Boris Johnson”. as well as forums and other web material. Sentiment analysis (also known as opinion mining) refers to the use of natural language processing, text analysis and computational linguistics to identify and extract subjective information in source materials. The analysis aimed to capture how often each candidate was discussed, how often individuals mentioned them, as a measure of “passion”, and the ratio of positive and negative language used. Mr Johnson’s relatively large lead in Google searches this time around  reflected not only voters’ intentions but also a well-run digital campaign.

Outline Social Network Online Social Networks Community Structure Rumor Blocking Power Law 1. Brief overview of social networks 2. How to build applications on top of the social network –  Think about a social network being MS Windows, We can build applications on it.

Question 1? Does Six Degrees of Separation imply six degrees of influence? Being connected via six degrees of separation doesn’t mean that these connections are socially meaningful. Influence in social networks has a limited, finite range. Actually, influence dissipates as a function of distance, for some social processes influence may permeate up to 3 degrees.

Three Degrees of Influence in friendship network

Three Degrees of Influence In Book Connected by Nicholas A. Christakis and James H. Fowler.

Three Degrees of Influence The influence of actions ripples through networks 3 hops (to and from your friends’ friends’ friends). Everything we do or say tends to ripple through our network, having an impact on our friends (one degree), our friends’friends (two degrees), and even our friends’ friends’ friends (three degrees). Our influence gradually dissipates and stops after three degrees. They from various domains, such as gaining weight, happiness, and politics.

I am happy! If I can affect my friends, then affect my friends' friends, and so on.  However, the effect seems to no longer be meaningful after three steps.

Question 2? How to explain Six Degrees of Separation and Three Degrees of Influence?

Community People in a same community share common interests in - clothes, music, beliefs, movies, food, etc. Influence each other strongly. People in a same community share common interests in the same brand of clothes, same kind of music, movies, food, etc. They influence each other strongly. Therefore, within three steps, the influence is strong. When companies focus first on meeting the needs of the people they serve, they don’t have to spend big money to attract new customers. And when they stay close to their communities they don’t need market research to tell them what people want. innovation

Community without overlap Community with overlap Community Structure Community without overlap Community with overlap * same color, same community

Community Structure In the same community, two nodes can reach each other in three steps. A few of tied key persons: C, D Member A reaches Member B via A-C-D-B Each community has a group of key persons who keep this community in certain stability. All members are surround those key persons. Usually, key persons know each other. Thus, each member A can reach another member B by at most three steps: In the first step, A reaches a key person C; in the second step, key person C reaches another key person D; in the third step, key person D reaches member B.

Community Structure For different communities, Two nodes may have distance more than three. Usually, the influence is weak outside the community. This is why the influence dissipates rapidly after 3 steps.

Community Structure For two overlapping communities, Two nodes can reach each other by at most six steps. A Often, two communities are overlapping because many persons have multiple interests. For example, … B C

Outline Social Network Online Social Networks Community Structure Rumor Blocking Power Law 1. Brief overview of social networks 2. How to build applications on top of the social network –  Think about a social network being MS Windows, We can build applications on it.

When misinformation or rumor spreads in social networks, what will happen? 11/7/2017

A misinformation said that the president of Syria is dead, and it hit the twitter greatly and was circulated fast among the population, leading to a sharp, quick increase in the price of oil. http://news.yahoo.com/blogs/technology-blog/twitter-rumor-leads-sharp-increase-price-oil-173027289.html 11/7/2017

In August, 2012, thousands of people in Ghazni province left their houses in the middle of the night in panic after the rumor of earthquake. http://www.pajhwok.com/en/2012/08/20/quake-rumour-sends-thousands-ghazni-streets In August, 2012, thousands of people in Ghazni province left their houses in the middle of the night in panic after the rumor of earthquake, which said that a major earthquake would hit the area until 5 am [3]. Believing in it, many people from the Ghazni city and some other districts of the province left their house and spent the whole night outside. The panic spread by the rumor was so intense that the people, who were in thousands, did not dare to return to their houses till morning. Mirwais, a resident of Ghazni city, talked to a news agency about this announcement. Later, the imams of the mosques had started believing in it and according to the statement made by Mirwais, Then, imams of mosques also started announcing about the earthquake. 11/7/2017

Influence each other strongly. People in a same community share common interests in - clothes, music, beliefs, movies, food, etc. Influence each other strongly. 11/7/2017

Rumor Blocking Problem 7 6 9 5 8 10 3 4 11 2 1 Yellow nodes are bridge ends. 12 14 13 11/7/2017

Example Two kinds of influence cascades: rumors and protectors. 6 protector 2 rumor 1 5 Two kinds of influence cascades: rumors and protectors. Each individual has three status: inactive, rumored, protected. The active individual activates all of its neighbors successfully. When rumors and protectors influence an individual at the same time, then the individual is protected. Each individual only has one chance to influence their neighbors. A node will never change its status if it has been activated. 3 4 1 is a rumor, 6 is a protector. Step 1: 1--2,3; 6--2,4. 2 and 4 are protected, 3 is infected. 11/7/2017 56

Example 6 2 1 5 3 4 Step 2: 4--5. 5 is protected. 11/7/2017

Least Cost Rumor Blocking Problem (LCRB) Bridge ends: form a vertex set; belong to neigborhood communities of rumor community; each can be reached from the rumors before others in its own community. C0 Red node is a rumor; Yellow nodes are bridge ends. C2 C1 11/7/2017

Set Cover Problem 7 6 9 5 8 10 3 4 11 2 1 Yellow nodes are bridge ends. 12 14 13 11/7/2017

Greedy Algorithm

Outline Social Network Online Social Networks Community Structure Rumor Blocking Power Law 1. Brief overview of social networks 2. How to build applications on top of the social network –  Think about a social network being MS Windows, We can build applications on it.

What is Power Law Graph?

Community Structure Less nodes with higher degree and more nodes with lower degree. All peoples are surround leaders.

Power Law During the evolution and growth of a network, the great majority of new edges are to nodes with an already high degree.

Power-law distribution Log-log scale: log f(x) ~ –αlog x Power law distribution: f(x) ~ x–α

Power Law Nodes with high degrees may have “butterfly effect”. Small number Big influence a small change at one place can result in large differences in a later state.

Important Facts on Power-law Many NP-hard network problems are still NP-hard in power-law graphs. While they have no good approximation in general, they have constant-approximation in power-law graphs.

References

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