Post 4: Social differentiation and Status Hierarchies

Review

In lecture 7-9, we learnt some methods of social network analysis, and many of them are related to graph & matrix theory. I have learnt some graph theories in high school, so I was interested in these measurements.

A social network can be represented as a graph, in which each node represents a person in the network. For ease of computation, this graph can be also represented as a matrix. Some characteristic measures in graph include nodal degree, density, geodesics, cut-point, bridge, clique, centrality and prestige etc. These different values show different characteristics of a social network, and some show the extent of importance of each node in the graph. For example, the degree centrality in a graph measures the links a node connects to others (divided into in-degree and out-degree in directional graphs), and closeness centrality measures the average geodesic distance from one node to the others.

The different measures are inspiring to me, which can conclude a complicated social network diagram into a few matrices and numbers!

When eigenrumor was being discussed, I was especially interested in the differences in ranks of blogs, and hence want to know more about social differentiation.

Topic: Social differentiation and Status Hierarchies

Phenomenon

As discussed in class, there are always some “core” people in a group, who always contribute a lot to discussion and also receive a lot of attention. In contrast, there are a lot more people discuss less and rarely noticed by others. In Hong Kong, the latter are called CD-ROM (because they are so-called “read-only”); in mainland, they are called people who read but never reply (看帖不回帖), which is usually a pejorative term.

Actually, in many social networks I have been, I am an “outsider”. But in a few social networks, I have achieved the “core” position, from my point of view. One of them is an online game which is not well known, so the players’ community is relatively small. Since I was once very active in the discussion board, my in-game-name was known by a lot of people even though I had never played with them. Below are some examples taken from Baidu Tieba, shows that there are some people recognized me and asked me questions even unrelated to the theme of the post.

Formation

Since I was once a well-known person in a community, I can tell how to become such a person.

The key is to first give out more significant and useful information. From my experience and observation, people tend to respond to those who they know well, rather than a stranger. Therefore, it is common that a post from a new user just received few replies. Hence, in a social community, as long as you give out enough significant and useful information, you will be noticed by others gradually, and then get back more response.

If we use in-degree and out-degree to measure a person’s participation in an (online) community, in-degree represents messages/replies one receives from others, and out-degree represents messages/information on gives out to others. When one increases his out-degree to a significant amount, his in-degree will increase and increase gradually, and subsequently he may be the one in the center. For the others, since they devote less effort in the participation, their in-degree and out-degree will keep at a low level, and maybe they will keep in a coterie which just includes a few people and only discuss with themselves, or will be isolated by the community.

Therefore, I think in-degree and out-degree are related, and they will be about the same eventually, as they show the activeness of a person towards this community. Take our blog circle as an example! I collected 2 sociograms below, one of which was taken from lecture notes in week 7, and the other was just grabbed from Guan Hao’s work [1]. In the first sociogram, we can see there are people who gave out a lot of comments but received less (e.g. Ling Luo), but people who receive a lot of comments usually gave out a lot (e.g. Su Jing). Now let’s look at these people in the second diagram. Since the diagram is already hard to read, I just post the data here: Ling Luo in-17 out-20, Su Jing in-25 out-24, and some new centers: Silu Li in-25 out-32, youniting in-10 out-21. We can see the “old centers” are already with almost same in-degree and out-degree, but “new centers” are with out-degree more than in-degree. It is due to time lag for others to know about them. I believe that when time passes, the in-degree and out-degree will become similar!

Impact

When a person is over well-known, his fans will wrongly believe that every word he says is correct. Nowadays, after a famous people post something on twitter or weibo, most of the comments are positive, and we can seldom see a comment doubting him. For example, below is a weibo post from Kai-Fu Lee(李開復)[2], and most of the comments are positive. Only one doubted him, “then why you argued with others?” Such a celebrity effect leads people tend to agree with their “idols”. We need to think independently, not according to the celebrity; especially he is not the authority in that area!

Reference:

[1] http://blogosphere.id3.cc/sociogram
[2] http://weibo.com/1197161814/z6PKso3qs

Post 3: Group Behavior

In lecture 5 and 6, we talked about psychology in group behaviors and collaboration.

In the class, we had an activity to see the difference of working on our own and collaborating in a group. We were first required to read an article about social cloud computing, and answer two questions. At the same time, we need to highlight words or sentences that seemed to be important. Subsequently, we need to combine it in our group and see how our answers varied. The combined file can be reached here: [1].

1. What is the definition of Social Cloud?
A Social Cloud is a resource and service sharing framework utilizing relationships established between members of a social network.
More comment: Social Cloud can provide some kinds of services and these services are actually provided and maintained by a social network instead of centralized servers. The type of the services does not matter, it can be computational work, storage, collaborative… therefore there are lots of applications listed in this article. As long as the services are provided by a social network and it utilizes the relationships established in a social network, it is considered as a Social Cloud.
2. What are the possible applications of a Social Cloud?
Ø A Social Computation Cloud
Ø A Social Storage Cloud
Ø A Social Collaborative Cloud
Ø A Social Cloud for Public Science
Ø An Enterprise Social Cloud

Our answers were all the same except Guan Hao, who gave some further more explanations. In addition, the bold parts in the document were the parts which we all highlighted, and the underlined parts were those just one of us highlighted.

Epistemic aim & epistemic cognition

When doing individual work, my epistemic aim was more of acquiring a “true” answer. However in group work, we tended to find out more different opinions and wanted to justify our belief. When people are getting together, their epistemic aim & cognition changes since different people may come up with different ideas, and we tend to exchange them.

Approach

In individual work, we usually form knowledge based on our own understanding of the resource. In contrast, during group work, we tend to exchange ideas, as written above. Thus interpersonal process acts as an important role. By exchanging ideas, we may make some justifications or corrections on our original answers, and tend to integrate it into a more completed one.

In conclusion, there is a lot of difference when we are doing individual work and group work, due to the interesting situation when people are communicating with each other. When people are exchanging ideas, they are affecting each other’s’ thoughts at the same time!

Reference:
[1] https://docs.google.com/document/pub?id=1rHsQ8OxFe9RwTuGwVZFmnU5m7cqF1rq6cMjCNg1Lip4

Post 2: Self-Presentation

Review

In the third lecture, we mainly focused on the psychology of human beings. We first had an overview of human activity in social network, and then talked about the information processing procedure of human. It is very interesting to me that there are such many sub-categories of memory, and I am very curious that how our brain process memory and classify it. After that, we learnt about the hierarchy of cognition. I have never considered that human’ knowledge is a higher level than information processing, and I would like to consider it more from now on.

In the fourth lecture, we talked more about the human psychology in society, especially social networks. We learnt the social cognition theory, which is about how people learn from others, and then discussed collaboration in social network. Actually, from my various observations in life, I can feel people’s behavior is like what is stated in the social cognition theory, but it was the first time I came across the theory. It brought me to a brand new world of psychology!

Today’s Topic: Self-Presentation

The theories match my observations in life. Among these, I am most interested in self-presentation.

Self-presentation is the way that an individual represent him/herself, to match the impression that he/she want to leave to others. This concept was brought out by Erving Goffman (1922-1982) in his book The Presentation of Self in Everyday Life [1]. In his opinion, life is like a stage and people are like the actors on it. People judge how the others expect according to different situations and act to build their image.

Strategies

There are mainly 5 different ways (strategies) of self-presentation. 1) Self-promotion is trying to make others think you are competent or capable, which is usually used when one is proposing a job vacancy. 2) Ingratiation is trying to make others like you, for example, always praise or flatter others. 3) Intimidation is trying to make others think you are dangerous or dignified, and obey you, for example, a boss showing anger explicitly may make his colleagues work harder. 4) Exemplification is trying to let other respect you as a model, such as doing something moral apparently. 5) Supplication is trying to get others’ sympathy, such as stating yourself as helpless and needy. Besides, there are some other ways of self-presentation. One is called self-handicapping, which is stating there is an obstacle in front of you, then, if you succeed finally, it is because you overcome it; if you failed, it is because the obstacle.

Posting encouraging status - I think it is an example of exemplification


Posting “I’m sick” - an example of supplication, which is usually seen on Facebook

If you ask, which kind do I belong to in most situations? I think I am more of the kind of Ingratiation. When discussing with others, I seldom express different opinion towards others, even though they have a totally different view from me. Although people may apply different strategies in different situations, I seldom apply other strategies. Maybe it is because I have not interacted with others completely and have not come across enough situations!

Motivation

There are different reasons for self-presentation. Firstly, people want to leave good impression to others, and build good image of themselves, this is the basic motivation. Secondly, when one possesses negative emotion, self-presentation of a positive image can help to regulate it, by encouraging positive emotion and restrain negative emotion. Thirdly, due to need for belong, people need to show the membership of the group by presenting they are similar to each other. Fourthly, due to self-esteem, being respected by others or cared by others make people feel good, and self-presentation is one of its main sources.

Effect on Social Networking

On social networking, it is more easy to use self-presentation, especially when one is going to pretend differently from how he/she behaves normally. The reason is that the ways we communicate on social network is limited due to technology so far. For example, we mainly use text and picture on Facebook, twitter etc. Although some software allow us use different ways, such as video, people online can just see a part of us, which is easier to pretend, compared to a community in everyday life.

For example, when more and more lovers “show-off” what they do together on Facebook, men who are single are feeling lonely, because they still cannot find their Ms.right. There is even a Japanese guy who invented a way to pretend to have a lover [2]. See the picture below, he takes photo by himself but makes the photo look like taken by his girlfriend! Although most of the readers think it is useless to pretend to be in love, but it proves that pretending is very easy on social network.

Self-presentation can be seen as a kind of art and it is very hard to explain it fully in such a short paragraph. If you have any doubts, questions or comments, please leave it here and I am looking forward to it! =)

Reference:

[1] Erving Goffman, The Presentation of Self in Everyday Life, Anchor Books, 1959
[2] Self Portrait With an Imaginary Girlfirend

Post 1: Derived Social Recommendation

Review

In the first lecture, we had an overview about social media and social networking. From the lecture, I learnt about different characteristics of social networking, such as the user age. And I found that mobile apps are bringing more and more influence to people in daily life, especially in the aspect of social networking.

In the second lecture, we discussed about some kinds of social tasks and social media, and then go to social media marketing. I was surprised to found that there are already a large number of different social tasks in our life, and various companies and people are benefited by ideas provided by different individuals.

My Topic: Derived Social Recommendation

I am especially interested in the topic of derived social recommendations. Along with the rapid development of different social networking applications, techniques of derived social recommendations are applied more and more widely. Derived social recommendation is a system used to provide different recommendations to different individuals according to their personalized information.

Types and Applications

There are different types of derived social recommendations: collaborative filtering (including user-based filtering and item-based filtering) and content-based filtering. Let me show you some applications with these different types.

For user-based filtering, it groups similar users and find out what they like, and then recommends items that a lot of users like to another similar user. For content-based filtering, it groups similar items and recommends high correlated items to individuals. Such collaborative filtering is used on people who indicated their “targets”, for example, friends relations like Facebook, product purchase records like Taobao and Amazon, and music sharing platform like Douban FM, Last.fm. The advantage of such filtering is that it provides personalized choice to users, and you can find what you like easily by this system. The more items you indicated that you like, you will get more customized recommendations.

A part of recommendation page of Taobao, obviously using user-based filtering.

My friend recommendation interface of the app “LINE”, although I don’t know which collaborative filtering it is using, I still see some friends’ name (and I don’t have their numbers!) This is because I have a lot of common friends with them.

For content-based filtering, it relies more on an item called “tag cloud”. When you read a piece of blog or news article, for example, an article introducing Hong Kong food, you will see recommended articles about Hong Kong food too. This is because they have similar tags, and system tends to mark them as high correlated items. Of course, they are more applied on news sites, blog providers, since they are usually described in words. However, other contents can also apply this system as long as they can be described in words and categories! Its advantage is obviously that it doesn’t rely heavily on the “user-target” relationship, and you don’t need to indicate a lot of items you like in order to see a new one. But it may need more artificial work, such as tagging the items.

A news article and its related articles grabbed from Yahoo! (Original Article)

Drawbacks It Causes

Well, benefits it brings are well-known: it helps people discover new items they like easily. Therefore, I will talk more about its drawbacks.

1. Biased information

Do you know that your internet browser is filtering your information when you are unconscious? If you don't believe, just open Google and search a keyword, then ask a friend in another country to do so, you will find the results are different. The author Eli Pariser expresses his worry in his book The Filter Bubble: What the Internet is Hiding From You [1]. When the internet presents a biased world to you, your view will also be biased. For example, if you are politically radical, and you may find all radical post on Facebook, and conservative views will be hidden. This is somehow scary since you will be more and more radical, and may finally fail to judge fairly. In another way, does this process make people separated into different circles and communicate different ideas less and less?

2. Inappropriate tags

As I mentioned above, in content-based filtering, more artificial work may be needed such as tagging items. For simplicity purpose, many websites let users do the work of tagging by themselves, like blog providers will let the blog holders tag their own articles. Another example is Douban FM, which develops an application called Doublo and encourages users to tag music in a game. However, when users’ goal is to achieve more coincidence tags, they may just try words randomly, regardless of whether the word can represent that piece of music. Hence, we can see that, due to various reasons, users may tag items inappropriately. When an item is tagged inappropriately, it may encounter difficulties in matching users and items.

Description about Doublo

OK, I will end my topic here. Thank you for reading this piece of article and all comments are welcomed! =)

Reference:

[1] The dangers of the internet: Invisible sieve, The Economist

Hi everyone!

I am currently a student of the MScIE programme. Before I joined this programme, I was a student in CUHK studying Quantitative Finance and Risk Management Science.

I started my blog from October 2005 with writing several sentences (full article sometimes) each post. But I would like to keep my blog as a private place, so I will give you the link of it when you are my good friend. :)

All comments are welcomed and I will reply them one by one. Hope we can all learn more together!