Introduction

6Tribes: Interest Focused Social Network.

6Tribes was a new aged social media app, that put user interests at the heart of connectivity; rather than who you know, it’s about what you know and what you want to know.

Lead Data Scientist + User Researcher | 6Tribes | 2016 | Acquired to become DriveTribe

Data

To handle the cold-start problem, we decided to lean on the giant of social media – Facebook. By using Facebook, we were able to allow users to provide us with permission for photos, locations, current groups and recent posts. After some research and user testing, we discovered Facebook profile data was aged and not very relevant.

The data is seemingly updated as a one time process, whilst the user creates an account. Although ironic, to use Facebook data as we tried to build a social media platform, there is a large degree of enrichment and unlocked potential in the data.

-      A lot of the data we used wasnatural language, from posts and groups. Context often played an important partin determining interest level.

-      NLP techniques were used with an iterative approach. We begun exploring a series of techniques on longer documents including bag of words, n-grams and TF-IDF. This worked for webpages,but not for posts due to often being much shorter in nature, in which we used the Rapid Automatic Keyword Extraction (RAKE) along with stop words and delimiters.

-      Further to this, on longer documents, we used Topic Extraction, using LDA. This is based from the theory each document has a multinomial distribution of topics, matched to a multinomial distribution of words. The documents can assumed to be a mix,assuming the nature in content variety that is posted in Facebook, to therefore generate content.
-      A main limitation of topical modelling is the topics are extracted words. We needed to manually create a mapping ontop of both topics and the RAKE extractor, to interests themselves.For example. If someone expresses interest in football, cricket, tennis then this implies a hobby of sport, as well as specific hobbies.  

Photos + Geo Information:

-      By using geo data from photos, you can determine the type of location such as tourist attraction,coffee shop and similar.

-      Posts: posts can indicate key interests, not only through keywords, but also additionally ifexternal links, events and locations are shared. With external public links, we were able to analyze the contents of such a link.

-      Groups: Here we were able to extract key themes from public posts within groups, indicating key discussion points and again interests.

Features

Social DNA

Across apps that present recommendations, users are often intrigued as to why an item has been recommended, even furious if a recommendation is incorrect. With Social DNA, we wanted to present users back their transformed data in a meaningful way hence did this via profile tags of their inferred interests. Users could then additionally delete and add tags, which allowed a feedback loop for algorithmic improvements.

Invite Game

Most apps make it easy to share assets and invite users via a array of platforms. However, with the use of Facebook, we were able to make contact invitation more intelligent. Through using Facebook we can see the connected friends whom has liked a post. If this is a repeated occurrence, this creates a weak signal they may also have this as a common interest. Hence the 6Tribes user, upon wanting to share can have more intelligent invitee recommendations. The invitee then becomes more willing to join, as the content itself appears relevant to them.

Recommended Tribes

From collated interests we recommended Tribes. These were formed based on interest weighting, alongside business and marketing objectives to appease to our growing user base. We matched using ElasticSearch matching and creating custom scoring based on both extracted interests. Tribes also contain keywords evolved in a similar process we’ve discussed above, allowing us to reinforce and evolve based on member postings.

Trending Tribes

To ensure we had a good onboarding process for users, we additionally created Trending Tribes, by analyzing frequency of posts and replies, per Tribe.

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Customers Said...

Delan

iOS, App Store

Just like Facebook and all those other apps but awesomer –

Anon

iOS, App Store

I love this app so much I’ve gotten to meet some really cool people from here and their all amazing :D It’s really cool how you can findsomeone who has similar interest in things as you by making a tribe or joiningone.

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