A social network diagram displaying tribes clustered by friendship ties among a set of Facebook users
The term tribe or digital tribe is used as a slang term for an unofficial community of people who share a common interest, and usually who are loosely affiliated with each other through social media or other Internet mechanisms. The term is related to "tribe", which traditionally refers to people closely associated in both geography and genealogy. Nowadays, it looks more like a virtual community or a personal network and it is often called global digital tribe. Most anthropologists agree that a tribe is a (small) society that practices its own customs and culture, and that these define the tribe. The tribes are divided into clans, with their own customs and cultural values
that differentiate them from activities that occur in 'real life'
contexts. People feel more inclined to share and defend their ideas on social networks than they would dare to say to someone face to face. For example, it would be ridiculous to 'poke' someone in real life.
History
The term "tribe" originated around the time of the Greek city-states and the early formation of the Roman Empire. The Latin term "tribus" has since been transformed to mean "A group of persons forming a community and claiming descent from a common ancestor"
(Oxford English Dictionary, IX, 1933, p. 339, as cited in Fried, 1975,
p. 7). As years passed by, the range of meanings have grown greater, for
example, "Any of various systems of social organization comprising several local villages, bands, districts, lineages, or other groups and sharing a common ancestry, language, culture, and name" (Morris, 1980, p. 1369). Morris (1980) also notes that a tribe is a "group of persons with a common occupation, interest, or habit," and "a large family." Vestiges of ancient tribe communities were preserved in both large gatherings (like football matches) and in small ones (like church communities). Even though nowadays the range of groups referred to as tribal is truly enormous, it wasn't until the industrial society eroded the tribal gatherings of more primitive societies and redefined community. However, the existence of social media as we know it today is due to the post-industrial society that has seen the rapid growth of personal computers, mobile phones and the Internet. People now can collaborate, communicate, celebrate, commemorate, give their advice and share their ideas around these virtual clans that have once again redefined the social behaviour.
The first attempt of such social communities dates back to at least 2003, when tribe.net was launched.
tribe.net starting point
Tribe Networks is the driving force behind tribe.net, which is a website similar to other social networking
sites. Users can create their own profiles and join networks, called
'tribes', based on common interests. Moreover, members can post job
offers and event recommendations. Tribe serves 50 metropolitan markets, its largest being the San Francisco Bay Area, Los Angeles, Washington, D.C., and New York City. The firm was found in July 2003 by Mark Pincus, Paul Martino and Valerie Syme, with the goal of connecting local people for what Pincus described as "an
online cocktail party where people are getting leads through their
friends. So people are there to have fun and connect and meet new
people." Soon the site caught the attention of Knight Ridder, The Washington Post Company and blue chip venture firm Mayfield, which both totally invested around $6.3 million in venture capital.
After three months of activity, Tribe brought together 48,000
registered users and 6,900 distinct tribes, earning revenue from job
postings and class fields.
Tribes from a technical perspective
Not only do Twitter tribes have mutual interests, but they also share potentially subconscious language features as found in the 2013 study by researchers from Royal Holloway University of London and Princeton.
Dr. John Bryden from the School of Biological Sciences at Royal
Holloway states that it is possible to anticipate which community
somebody is likely to belong to, with up to 80 percent accuracy. This research shows that people try to join societies based on the same interests and hobbies.
In order to achieve this, publicly available messages were sent via
Twitter to record conversations between two or more participants. As a
result, each community can be characterised by their most used words.
This approach can enrich new communities detection based on word
analysis in order to automatically classify people inside social networks. The methods of identification of tribes relied heavily on algorithms and techniques from statistical physics, computational biology and network science.
A different approach is taken by Tribefinder. The system is able to identify tribal affiliations of Twitter users using deep learning and machine learning. The system establishes to which tribes individuals belong through the analysis of their tweets and the comparison of their vocabulary.
These tribal vocabularies are previously generated based on the
vocabulary of tribal influencers and leaders using keywords expressing
concepts, ideas and beliefs.
The final step to make the system learn on how to associate
random individuals with specific tribes consists of the analysis of the
language these influential tribal leaders use through deep learning. In
so doing, classifiers are created using embedding and LSTM
(long short-term memory) models. Specifically, these classifiers work
by collecting the Twitter feeds of all the users from the tribes that
Tribefinder is training on. On these, embedding
is applied to map words into vectors, which are then used as input for
the following LSTM models. Tribefinder analyzes the individual’s word
usage in their tweets and then assigns the corresponding alternative
realities, lifestyle, and recreation tribal affiliation based on the
similarities with the specific tribal vocabularies.
An in-depth look into the research
The research had four main stages on which it focused: background, results, conclusions and methods.
Background
The language is a system of communication consisting of sounds, words, and grammar, or the system of communication used by people in a particular country or type of work. Language is perhaps the most important characteristic that distinguishes human beings from other animals. In addition, it has a wide range of social implications that can be associated with social or cultural groups.
People usually group in communities with the same interests. This will
result in a variation of the words they use because of the
differentiation of terms from each domain. Therefore, the hypothesis of this study would be that this variation should closely match the community structure of the network. To test this theory, around 250,000 users from the social networking and microblogging
site Twitter were monitored in order to analyse whether the groups
identified had the same language features or not. As Twitter uses
unstructured data and users can send messages to any other users, the
study had to be based on complex algorithms. These algorithms had to
determine the word frequency inside messages between people and make a
link to the groups they usually visited.
Results and discussion
The problem of detecting the community features is one of the main issues in the study of networking systems. Social networks naturally tend to divide themselves into communities or modules. However, some world networks are too big so they must be simplified before information can be extracted. As a result, an effective way of dealing with this drawback for smaller communities is by using modularity algorithms in order to partition users into even smaller groups. For larger ones, a more efficient algorithm called 'map equation' decomposes a network into modules by optimally compressing a description of information flows on the network.
Each community was therefore characterised according to the words they
used the most, based on a ranking algorithm. To determine the
significance of word usage differences, word endings and word lengths
were also measured and showed that the pattern
found was the correct one. Moreover, these studies also helped in
predicting community membership of users, by comparing their own word
frequencies with community word usage. This helped in forecasting which
community a certain user is going to access based on the words that they
are using.
The proportion of users whose topological community association is correctly predicted by the study.
Conclusions
An illustration of the method for predicting which community a user is embedded in.
The aim of this research was to study the bond between community
structure in a social network environment and language use within the
community . The striking pattern that was found suggests that people
from different clans tend to use different words based on their own
interests and hobbies. This study can show how people make friends based on the same vocabulary range that they use.
Even though this approach didn't manage to cover all people inside
Twitter, it has several advantages over ordinary surveys that cover a
smaller scale of groups: it is systematic, it is non-intrusive and it
easily produces large volumes of rich data.
Moreover, other cultural characteristics can be found out when
extending this study. For example, whether individuals that belong to
multiple communities use different word sets in each of them.
Methods
A process called snowball-sampling helped forming the sample network. Each user's tweets
and messages were recorded and any new users referenced were added to a
list from where they were picked to be sampled. Messages that were
copies have been ignored. In order to find out the words that
characterise each clan, the fraction of people that use a certain word
was compared with the fraction of people that use that word globally.
The difference between communities has also been measured by comparing
the relative word usage frequency.
Last but not least, individual word usage was compared with each
community word usage to pick the best matching clan for individual
users.
Different language misspellings within tribes
Words, and the way we spell them are in a continuous change, as we find new ways to communicate. Despite the fact that traditional dictionaries don't take into account the changes, online ones have adopted many of them.
An interesting fact outlined in the research above is that communities
tend to use their own misspelt words. According to Professor Vincent
Jansen from Royal Holloway communities would misspell words in different ways, just as people have different regional accents. For example, Justin Bieber fans tend to end words in "ee" as in "pleasee", while school teachers tend to use long words. Moreover, the largest group found in the study was composed of African Americans who were using the words "nigga", "poppin", and "chillin". Members of this community also had the common habit of shortening the ends of the words, replacing "ing" with "in" and "er" with "a".
The campfire
Each tribe has an online-platform (such as Flickr or Tumblr),
called campfire around which they gather. These campfires tend to
enable one or more of the following three tribal activities:
- Cooperation (e.g. Wikipedia)
- Communication (e.g. Social networks)
- Cognition (e.g. Blogs)
However, some brands are building their own tribes around platforms outside of these.
Cooperation
Cooperation is the action of working together to the same end.
Cooperation developed naturally over time, as it helped companies to
streamline their research costs and to better answer to users'
requirements. As a result, nowadays organisations are looking for
flexible structures that can easily adapt to this rapidly changing
environment. Groupware systems perfectly cater to these needs of companies. Informal communication predominates and specialists in certain domains exchange their experience with other people within the groupware environment. Collaboration and cooperation are available through instant messages; people can discuss, chat and swap ideas. Moreover, people can work together while they are located remotely from each other. Groupware can be split into three categories: communication, collaboration and coordination, depending on the level of cooperation and technology involved in the process. One of the biggest and well-known cooperation software is Wikipedia.
The logo of Wikipedia
Wikipedia
Wikipedia is a collaborative software
because anyone can edit it. You can edit articles, view past revisions
and discuss through a forum the current state of each article. Due to
the fact that anyone can change it and find information very quickly, it has become one of the 10 most accessed sites on the Internet.
Advantages
Wikipedia has many advantages over other encyclopedias:
- It's free and open for anyone on the Internet;
- All past edits and chats from the forum are public and everyone can see them;
- Updates happen frequently;
- It contains millions of articles;
- Easy to use and learn.
Disadvantages
However, there are also some drawbacks:
- Information can be inaccurate;
- It is open to spam and vandalism;
- Some articles can contain omissions and be hard to understand;
- It can be too open sometimes (for confidential documentation);
- It requires Internet connectivity.
Communication
Communication is the act or an instance of communicating; the imparting or exchange of information, ideas, or feelings. Communication has drastically changed over time and social networks have changed the way people communicate. Even though people]can interact with each other 24/7, there is a new wave of barriers and threats. In the workplace
environment, electronic Communication has overtaken face-to-face and
voice-to-voice Communication by far. This major shift has been done in
advantage of Generation Y, who prefer instant messaging than talking directly to someone. It is often said that it could become an ironic twist, but social media has the real potential of making us less social.
However, there are studies that confirm that people are becoming more
social, but the style in which they interact with each other has changed
a lot. One of the major drawbacks of social networks is privacy, as people tend to trust others more rapidly and send more open messages about themselves. As a result, personal information can be easily exposed to other persons. Twitter and Facebook are two of the biggest social networks in the world.
Facebook
is currently the largest social network in the world with more than 1
billion people using this website. This actually means that one in seven
people on Earth use Facebook.
Facebook users share their stories, images and videos in order to
celebrate and commemorate events together. They can also play social games and like other Facebook pages. Moreover, there is also a section called 'News Feed' where users can see social information from their friends
or from the pages that they liked or shared. Each user has their own
profile page that is called 'wall', where they can post all the
above-mentioned materials (their friends can do this as well). The biggest advantage of Facebook is that you can make new friends, as well as find old acquaintances and restart socialising with them. One of the most useful feature of Facebook is the existence of groups.
Users with the same interests can create a new group or take part in
already existing ones to debate information and exchange their ideas.
However, there are also groups that are created to declare an
affiliation, such as an obsession for different subjects.
Twitter
is another social network that allows users to send and read short
messages called 'tweets'. Even though messages can contain only 140
characters, this is the perfect length for sending status updates to
followers. The main advantage of Twitter is that people can gain followers quickly and share ideas and links very fast. There are networks of influential people who can be connected via Twitter.
On Twitter, tribes manifest themselves as followers of either a person,
a company or an institution. As a result, it can be used as a marketing tool to make someone's product
visible, on condition that a big tribe of followers is created. In
order to do this, the right community must be built, as finding the
right people can be a challenge.
There are some steps that users could take into account in order to
make connections and therefore make people follow them: search using
Twitter search, follow the followers of other users, look at Twitter
Lists, use #Hashtags and find third-party programs.
Cognition
Cognition is the mental action or process of acquiring knowledge and understanding through thought, experience and senses. People like to share their ideas and gather together via blogs. A blog is an online journal
where people express themselves and want to get their voice heard.
People tend to frequent blog communities due to the fact that they offer
specific information in which the reader is interested. There are also business
blogs that can be used to share information within a company. These can
be used as a flexible medium, where employees can be informed about
topics that can range from the use of new technology to the company policies. On blogs, people tend to gather in tribes or clans
if they find information that can satisfy their interests. In order to
accomplish this goal, bloggers title their postings in such way that
they can catch people's attention.
The biggest advantage of blogs is that bloggers tend to help each other
when someone feels at a loss due to the fact that some bonds might have
been created inside the community.
Conclusion
As Seth Godin states, "The Internet eliminated geography". People join tribes or clans because they find and share the same ideas and interests with other people.
The main disadvantage of old tribes is that they couldn't influence
group behaviour. On the other hand, new tribes are self-sustaining and
can survive without a leader, they are not necessarily dialogue based
and they are long lasting. As it has been demonstrated within this
article, tribes have influenced the way languages, organisations and
cultures work. They have redefined old concepts with the help of social media and have changed the way people will interact in the future.
