User profile learning, such as mobility and demographic profile learning, is of great importance to various applications. Meanwhile, the rapid growth of multiple social platforms makes it possible to perform a comprehensive user profile learning from different views. However, the research efforts on user profile learning from multiple data sources are still relatively sparse, and there is no large-scale dataset released towards user profile learning. In our study, we contribute such benchmark and perform an initial study on user mobility and demographic profile learning. First, we constructed and released a large-scale multi-source multimodal dataset from three geographical areas. We then applied our proposed ensemble model on this dataset to learn user profile. Based on our experimental results, we observed that multiple data sources mutually complement each other and their appropriate fusion boosts the user profiling performance.
In this technical demonstration, we showcase the first ai-driven social multimedia influencer discovery marketplace, called SoMin. The platform combines advanced data analytics and behavioral science to help marketers find, understand their audience and engage the most relevant social media micro-influencers at a large scale. SoMin harvests brand-specific life social multimedia streams in a specified market domain, followed by rich analytics and semantic-based influencer search. The Individual User Profiling models extrapolate the key personal characteristics of the brand audience, while the influencer retrieval engine reveals the semantically-matching social media influencers to the platform users. The influencers are matched in terms of both their-posted content and social media audiences, while the evaluation results demonstrate an excellent performance of the proposed recommender framework. By leveraging influencers at a large scale, marketers will be able to execute more effective marketing campaigns of higher trust and at a lower cost.
The exponential growth of online social networks has inspired us to tackle the problem of individual user attributes inference from the Big Data perspective. It is well known that various social media networks exhibit different aspects of user interactions, and thus represent users from diverse points of view. In this preliminary study, we make the first step towards solving the significant problem of personality profiling from multiple social networks. Specifically, we tackle the task of relationship prediction, which is closely related to our desired problem. Experimental results show that the incorporation of multi-source data helps to achieve better prediction performance as compared to single-source baselines.
SoMin.ai was selected as one of the 19 top Singapore Content Marketing Companies and Startups by Best Startup.
The article showcased their top picks for the best Singapore based Content Marketing companies. The startups and companies that were shortlisted were based on them taking a variety of approaches to innovate the Content Marketing industry.
Digital advertising is when we pay to place messages in front of consumers across digital channels such as search, social media, and websites.
Like traditional advertising, digital advertising is pay to play:
You spend money to have your ad creative placed in front of consumers.
Unlike traditional advertising, however, digital advertising is a game played at light speed:
Ad space is bought and sold in real-time in auctions regulated by sophisticated machine learning algorithms.
Advertisers have the power to target granular audience segments using rich data from ad platforms on demographics and behaviors.
Platforms like Google and Facebook continually place, adjust, boost, and penalize ads based on ad quality and engagement.
Digital advertising gives brands an unprecedented ability to target, reach, and convert prospects at scale.
But there's a big problem...
This year, Artificial Intelligence has the ability to transform the marketing and advertising ecosystem as we know it. The World’s top 3 “Cool Vendors in AI for Marketing” were released in Gartner’s annual review October 5th, 2020, naming SoMin.ai, Cheq, and Qwarry as the world’s most innovative solutions utilizing AI to solve marketing’s biggest pain points. Previously, Gartner’s list featured Zoom, Movie, Cybereason, Snowflake, Gong, Datorama, Wrike, and many other leading SaaS unicorns.