Science & Press · Built by seasoned marketers and an AI professor
Science & Press: the research and coverage behind SOMIN
SOMIN's audience personas, creative scoring and competitor analytics come from research by co-founder Prof. Aleks Farseev and the SOMIN team, published at AAAI, ACM Multimedia, SIGIR, WSDM and The Web Conference, and in ACM TOIS.
Who builds SOMIN
Seasoned marketers and an AI professor, on one product
Prof. Aleks Farseev co-founded SOMIN after a PhD at the National University of Singapore on learning user profiles from many social networks at once. He is a research professor in digital-marketing AI, and his work on audience profiling, personality-driven recommendation and explainable AI for advertising is cited 577 times on Semantic Scholar (as of 2026-10-17).
Next to the research team, SOMIN's marketers turn those models into the playbooks brand and agency teams run every week: whitespace maps, personas and tensions, pre-scored concepts and content calendars.
Research profiles
- Google Scholar
- Forbes Technology Council
- e27 columnist
- Semantic Scholar
- ACM Digital Library
- DBLP
- farseev.com
Citation figures from Semantic Scholar, 2026-10-17.
From paper to product
Seven research lines that run inside SOMIN today
Each line of research below is a capability in the platform. Click a paper to read it on the publisher's site.
01Audience profiling from many data sources
How to learn who an audience is from posts, images, check-ins and sensors across several networks at once, and why the data source changes what a model learns.
- AAAI 2020 I Know Where You Are Coming From: On the Impact of Social Media Sources on AI Model Performance (Student Abstract)
- AAAI 2017 TweetFit: Fusing Multiple Social Media and Sensor Data for Wellness Profile Learning
- SIGIR 2017 Cross-Domain Recommendation via Clustering on Multi-Layer Graphs
- ACM TOIS 2017 Tweet Can Be Fit: Integrating Data from Wearable Sensors and Multiple Social Networks for Wellness Profile Learning
02Personality-driven content
Inferring an audience's personality from its content and using it to choose and generate the posts that audience responds to.
- ACM MM 2022 Personality-Driven Social Multimedia Content Recommendation
- Frontiers in Big Data 2022 Do we behave differently on Twitter and Facebook: Multi-view social network user personality profiling for content recommendation
- WSDM 2021 SoMin.ai: Personality-Driven Content Generation Platform
- ICMR workshop 2021 Two-Faced Humans on Twitter and Facebook: Harvesting Social Multimedia for Human Personality Profiling
03Scoring creative before launch
Predicting how an ad creative will perform from its text, image, targeting and settings, then explaining the score so a marketer can act on it.
- ACM TOIS 2025 Fusing Predictive and Large Language Models for Actionable Recommendations in Creative Marketing
- ACM MM 2023 Against Opacity: Explainable AI and Large Language Models for Effective Digital Advertising
- WSDM 2023 SoCraft: Advertiser-level Predictive Scoring for Creative Performance on Meta
04Explainable AI and LLMs for competitor analytics
Combining performance models with large language models to read competitors' communications and say why something works, not only that it does.
- WWW 2025 SOEX: Explainable AI for Competitor Communications Analytics
- ACM MM 2025 SOMIN: An Explainable AI and LLM Platform for Real-Time, Data-Driven Digital Marketing Strategy
- arXiv 2024 SOMONITOR: Combining Explainable AI & Large Language Models for Marketing Analytics
- ACM MM 2016 bBridge: A Big Data Platform for Social Multimedia Analytics
05Agentic AI and strategy co-creation
Agents that retrieve real context data before they write, so content stays distinctive instead of converging on the same generic output.
- SIGIR 2026 SOMIN: Agentic AI for Automating Professional Visibility and Countering Content Homogenization
- ACM MM 2025 MindFuse: Towards GenAI Explainability in Marketing Strategy Co-Creation
06Creator and influencer analytics
Finding the right creators and accounts, classifying social posts with less labelling, and telling personal, brand and celebrity accounts apart.
- ACM MM workshop 2021 Improving Multimodal Data Labeling with Deep Active Learning for Post Classification in Social Networks
- AAAI 2019 A Whole New Ball Game: Harvesting Game Data for Player Profiling
- ACM MM 2018 SoMin.ai: Social Multimedia Influencer Discovery Marketplace
- EGOSE 2018 Person, Organization, or Personage: Towards User Account Type Prediction in Microblogs
07Responsible AI in advertising
The ethics and privacy questions raised by automated profiling, ad targeting and generative creative.
In SOMIN today: How SOMIN handles personal data →Publications
Top-tier conference and journal papers
Full papers and journal articles at AAAI, ACM Multimedia, SIGIR and in ACM TOIS and ACM TIST.
- ACM TOIS · 2025 · Journal articleFusing Predictive and Large Language Models for Actionable Recommendations in Creative MarketingQi Yang, Aleksandr Farseev, Marlo Ongpin, Alfred Huang, et al.. ACM Transactions on Information Systems, vol. 43, pp. 1-31.
- ACM MM · 2022 · Full paperPersonality-Driven Social Multimedia Content RecommendationQi Yang, Sergey Nikolenko, Alfred Huang, Aleksandr Farseev. Proceedings of the 30th ACM International Conference on Multimedia (MM '22), Lisboa, pp. 7290-7299.Download PDF
- AAAI · 2017 · Full paperTweetFit: Fusing Multiple Social Media and Sensor Data for Wellness Profile LearningAleksandr Farseev, Tat-Seng Chua. Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), Technical Track: AI and the Web.Download PDF
- SIGIR · 2017 · Full paperCross-Domain Recommendation via Clustering on Multi-Layer GraphsAleksandr Farseev, Ivan Samborskii, Andrey Filchenkov, Tat-Seng Chua. Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '17), Tokyo, pp. 195-204.
- ACM TOIS · 2017 · Journal articleTweet Can Be Fit: Integrating Data from Wearable Sensors and Multiple Social Networks for Wellness Profile LearningAleksandr Farseev, Tat-Seng Chua. ACM Transactions on Information Systems, vol. 35, no. 4, pp. 1-34.
- ACM TIST · 2017 · Journal articleLearning User Attributes via Mobile Social Multimedia AnalyticsLiqiang Nie, Luming Zhang, Meng Wang, Richang Hong, Aleksandr Farseev, Tat-Seng Chua. ACM Transactions on Intelligent Systems and Technology, vol. 8, no. 3, pp. 1-19.
Papers, demos and abstracts at top venues
Papers, industry and demo papers, and student abstracts at ACM Multimedia, AAAI, SIGIR, WSDM, The Web Conference, ICMR, CLEF and WebSci.
- SIGIR · 2026 · PaperSOMIN: Agentic AI for Automating Professional Visibility and Countering Content HomogenizationAleksandr Farseev, Kirill Lepikhin, Kevin Manuel, Maksim Gorodilov, et al.. Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '26).
- ACM MM · 2025 · PaperMindFuse: Towards GenAI Explainability in Marketing Strategy Co-CreationAleksandr Farseev, Marlo Ongpin, Qi Yang, Ilia Gossoudarev, et al.. Proceedings of the 33rd ACM International Conference on Multimedia (MM '25), Dublin.Download PDF
- WWW · 2025 · Companion paperSOEX: Explainable AI for Competitor Communications AnalyticsAleks Farseev, Sergey Nikolenko, Qi Yang, Kirill Lepikhin, et al.. Companion Proceedings of the ACM Web Conference 2025 (WWW '25), Sydney, pp. 2823-2826.
- ACM MM · 2025 · Industry demoSOMIN: An Explainable AI and LLM Platform for Real-Time, Data-Driven Digital Marketing StrategyAleksandr Farseev. Proceedings of the 33rd ACM International Conference on Multimedia (MM '25), Dublin, industry demonstration.
- ACM MM · 2023 · PaperAgainst Opacity: Explainable AI and Large Language Models for Effective Digital AdvertisingQi Yang, Marlo Ongpin, Sergey Nikolenko, Alfred Huang, Aleksandr Farseev. Proceedings of the 31st ACM International Conference on Multimedia (MM '23), Ottawa, pp. 9299-9305.Download PDF
- WSDM · 2023 · Demo paperSoCraft: Advertiser-level Predictive Scoring for Creative Performance on MetaAlfred Huang, Qi Yang, Sergey Nikolenko, Marlo Ongpin, et al.. Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining (WSDM '23), Singapore, demonstration.
- WSDM · 2023 · Demo paper"Just To See You Smile": SMILEY, a Voice-Guided GUY GANQi Yang, Christos Tzelepis, Sergey Nikolenko, Ioannis Patras, Aleksandr Farseev. Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining (WSDM '23), Singapore, demonstration.
- WSDM · 2021 · Demo paperSoMin.ai: Personality-Driven Content Generation PlatformAleksandr Farseev, Qi Yang, Andrey Filchenkov, Kirill Lepikhin, et al.. Proceedings of the 14th ACM International Conference on Web Search and Data Mining (WSDM '21), demonstration.Download PDF
- AAAI · 2020 · Student abstractI Know Where You Are Coming From: On the Impact of Social Media Sources on AI Model Performance (Student Abstract)Qi Yang, Aleksandr Farseev, Andrey Filchenkov. Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), Student Abstract Track.Download PDF
- AAAI · 2019 · Student abstractA Whole New Ball Game: Harvesting Game Data for Player ProfilingIvan Samborskii, Aleksandr Farseev, Andrey Filchenkov, Tat-Seng Chua. Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), Student Abstract Track, pp. 10025-10026.Download PDF
- ACM MM · 2018 · PaperSoMin.ai: Social Multimedia Influencer Discovery MarketplaceAleksandr Farseev, Kirill Lepikhin, Hendrik Schwartz, Eu Khoon Ang, Kenny Powar. Proceedings of the 26th ACM International Conference on Multimedia (MM '18), Seoul, pp. 1234-1236.
- CLEF · 2018 · PaperMulti-view Personality Profiling Based on Longitudinal DataKseniya Buraya, Aleksandr Farseev, Andrey Filchenkov. Experimental IR Meets Multilinguality, Multimodality, and Interaction: CLEF 2018, Lecture Notes in Computer Science vol. 11018, pp. 15-27.
- AAAI · 2017 · Student abstractTowards User Personality Profiling from Multiple Social NetworksKseniya Buraya, Aleksandr Farseev, Andrey Filchenkov, Tat-Seng Chua. Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), Student Abstract Track.Download PDF
- ACM MM · 2016 · Demo paperbBridge: A Big Data Platform for Social Multimedia AnalyticsAleksandr Farseev, Ivan Samborskii, Tat-Seng Chua. Proceedings of the 24th ACM International Conference on Multimedia (MM '16), Amsterdam, pp. 759-761.
- ICMR · 2015 · Full paperHarvesting Multiple Sources for User Profile Learning: a Big Data StudyAleksandr Farseev, Liqiang Nie, Mohammad Akbari, Tat-Seng Chua. Proceedings of the 5th ACM International Conference on Multimedia Retrieval (ICMR '15), Shanghai, pp. 235-242.
- WebSci · 2015 · PaperCross-Social Network Collaborative RecommendationAleksandr Farseev, Denis Kotkov, Alexander Semenov, Jari Veijalainen, Tat-Seng Chua. Proceedings of the ACM Web Science Conference (WebSci '15).
Journals, workshops and preprints
- arXiv · 2024 · PreprintSOMONITOR: Combining Explainable AI & Large Language Models for Marketing AnalyticsAleksandr Farseev, Qi Yang, Marlo Ongpin, Ilia Gossoudarev, et al.. arXiv preprint arXiv:2407.13117 (not peer reviewed).Download PDF
- WSDM · 2023 · Talk abstractUnder the Hood of Social Media Advertising: How Do We use AI Responsibly for Advertising Targeting and Creative EvaluationAleksandr Farseev. Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining (WSDM '23), Singapore (talk abstract).
- Frontiers in Big Data · 2022 · Journal articleDo we behave differently on Twitter and Facebook: Multi-view social network user personality profiling for content recommendationQi Yang, Aleksandr Farseev, Sergey Nikolenko, Andrey Filchenkov. Frontiers in Big Data, vol. 5 (Original Research).Download PDF
- ICMR workshop · 2021 · Workshop paperTwo-Faced Humans on Twitter and Facebook: Harvesting Social Multimedia for Human Personality ProfilingQi Yang, Aleksandr Farseev, Andrey Filchenkov. Proceedings of the 2021 ACM Workshop on Intelligent Cross-Data Analysis and Retrieval (ICDAR @ ICMR '21).Download PDF
- ACM MM workshop · 2021 · Workshop paperImproving Multimodal Data Labeling with Deep Active Learning for Post Classification in Social NetworksD. Krylov, S. Poliakov, N. Khanzhina, A. Zabashta, A. Filchenkov, Aleksandr Farseev. Workshop on Multimedia Understanding with Less Labeling (MULL @ ACM Multimedia 2021).
- EGOSE · 2018 · PaperPerson, Organization, or Personage: Towards User Account Type Prediction in MicroblogsIvan Samborskii, Andrey Filchenkov, Georgiy Korneev, Aleksandr Farseev. International Conference on Electronic Governance and Open Society (EGOSE 2018).
- SIGWEB Newsletter · 2016 · Article360° user profiling: past, future, and applicationsAleksandr Farseev, Mohammad Akbari, Ivan Samborskii, Tat-Seng Chua. ACM SIGWEB Newsletter, 2016, pp. 1-11.
Articles
Forbes Technology Council and e27 columns by Prof. Aleks Farseev
Plain-language articles on the technology behind SOMIN: large language models, AI agents, explainable AI and ad optimisation for marketers, and on marketing measurement and Southeast Asian business for e27. Each opens on the publisher's site.
- Singapore and Romania don't need another MOU. They need first customerse27 · 2026
- Every dashboard is green. So why can't anyone say what worked?e27 · 2026
- 18 Powerful Applications Of AI Agents In MarketingForbes Technology Council · 2025
- Will AI Make Agencies Obsolete? The Future Of AdvertisingForbes Technology Council · 2025
- Prompting, Fine-Tuning, RAG And AI Agents For Future MarketingForbes Technology Council · 2025
- LLMs Vs. Small Neural Networks In Marketing: Is Bigger Always Better Or Is It About The Technique?Forbes Technology Council · 2024
- Eight AI-Powered Strategies To Transform Your Marketing StrategyForbes Technology Council · 2024
- Redemptive Marketing: The Path To Resolving Transparency And Performance Dilemmas In Digital AdvertisingForbes Technology Council · 2024
- Why Transparency Matters For Today's Marketing-Driven CompaniesForbes Technology Council · 2024
- Low-Funnel Ad Optimization On Social Media PlatformsForbes Technology Council · 2024
- Mastering Social Media Advertising: A Comprehensive Guide To Metrics And OptimizationForbes Technology Council · 2023
- Overcoming The Volatility Of Today's Ad PricesForbes Technology Council · 2023
- Beyond Chatbots: Harnessing The Power Of LLMs In BusinessForbes Technology Council · 2023
- Unlocking VC Investment: The Key Element For Large Language Model-Backed StartupsForbes Technology Council · 2023
- Can AI Have Intuition, And What Is So Special About GPT-4's Multimodality?Forbes Technology Council · 2023
- Is Bigger Better? Why The ChatGPT Vs. GPT-3 Vs. GPT-4 Battle Is Just A Family ChatForbes Technology Council · 2023
- Four Lessons I Learned Along A Rough Road To Becoming The CEO Of An AI StartupForbes Technology Council · 2023
- Will Machines Replace Human Creativity?Forbes Technology Council · 2022
- Closing The Gap Between Marketing And AI SystemsForbes Technology Council · 2022
In the press
SOMIN and its founders in the news
Interviews, profiles and customer stories about SOMIN and Prof. Aleks Farseev from independent publications, investors and partners. Each opens on the publisher's site.
e27 reports on SOMIN's recognition by Google DeepMind and its plan to rework AI-powered marketing.
CEO Insights Asia · 2025Prof. Aleks Farseev: Leading the charge in AI-driven digital marketing and strategic communicationsAn interview profile of SOMIN's co-founder and CEO on his career, AI marketing work and views on generative AI.
Google CloudSOMIN: a Google Cloud customer storyHow SOMIN uses Gemini and Google Cloud to shorten campaign analysis from days to minutes.
New In Asia · 2024How a pivot is done: childlike faith and insights shape SoMin.aiHow the company moved from ad optimisation to its SOMONITOR research tools.
Salt&Light · 2024How a child-like prayer for ducks laid the faith foundation for an AI start-upA profile of Prof. Aleks Farseev on how his faith and experiences shaped the business.
FG Ventures · 2023From academic research to adtech entrepreneurship: the journey of Aleks Farseev and Somin.AIAn interview on the move from academia to founding an AI advertising company, with startup lessons.
Joint Journey (JJ Capital)From academic research to AI-powered marketing: the inspiring journey of SoMin.ai's founderAn investor profile of the founder, the platform and the road from research to a company.
ITMO News · 2020ITMO professor Aleksandr Farseev on long tail marketing and the 2020 Gartner Cool Vendors awardAn interview on the Gartner Cool Vendor award, AI ad targeting and plans for 2021.
Talks and lectures
Keynotes, lectures and Marketing Mondays sessions
Prof. Aleks Farseev on AI in advertising, from ACM Multimedia and INSEAD to Marketing Mondays. Videos open on YouTube.
Startup pitch of SOMIN's four modules (competitor insight, gap-finding, concept generation, pre-launch ad scoring) with a Mothercare case study.
Industry expert talk · 2025Will AI Make Agencies Obsolete? Rethinking the Future of AdvertisingACM Multimedia 2025, Dublin (Industry Expert Talk IET #2); video on Marketing Mondays by SOMINCompares three ways AI is entering advertising (replacing, assisting and explaining creative work) and how agencies are adapting.
Keynote · 2025The Future of Generative AI in Marketing CommunicationsDigital Marketing Conference Kuala Lumpur 2025 (DMCKL2025); Marketing Mondays by SOMINKeynote on generative AI for audience segmentation and campaign building, using a Miraflora Wagyu case study with SOMONITOR and GWI.
Lecture · 2025INSEAD: How AI Cut Marketing Costs for a Beef BrandINSEAD lecture; Marketing Mondays by SOMINLecture on how AI consumer and competitor insights helped a US premium beef brand lower customer acquisition cost.
Lecture · 2025NUS Engineering: Business Strategy with GA4, Meta Ads & SOMONITORNUS Engineering (Business Engineering students); Marketing Mondays by SOMINClass session on Google Analytics 4, Meta Ads Manager and competitor insight with SOMONITOR.
Marketing Mondays · 2024Marketing Mondays: The Significance Of Responsible AI for Marketing Strategy & BeyondMarketing Mondays at Block71 Singapore; Marketing Mondays by SOMINFireside chat on the responsible use of large language models in marketing, co-hosted by Prof. Aleks Farseev at Block71 Singapore.
Talk · 2024The Intelligent Advantage: Large Language Models Redefining Marketing Decision-MakingTechnology for Marketing (YouTube channel)How LLMs speed up competitor, persona, brand-voice and pain-point analysis, and why they should support rather than replace marketers.
Demo · 2024SOMONITOR Demo - Travel Agents and Tourist Guides Industry Forum 2024Travel Agents and Tourist Guides Industry Forum 2024 (Singapore Tourism Board); SOMIN channelLive demonstration of SOMONITOR for the travel industry.
Podcast · 2023 · in Russian«Нужно разобраться со скиллами, с головой, а потом уже деньги искать» (You need to sort out your skills first, then look for money)MTS StartUp Hub, podcast «От сида до экзита» (From Seed to Exit)Russian-language interview on building SoMin.ai abroad, the venture downturn and whether LLMs are a real growth opportunity.
Demo · 2023SoMin.ai Platform DemoAlex Farseev (YouTube channel)Walkthrough of the SOADS (long-tail ad targeting) and SOMONITOR (creative scoring, SODA LLM assistant) modules.
Talk · 2023From Academic Research to Adtech Entrepreneurship: The Journey of Aleks Farseev and Somin.AIDigital Ignition - A Coworking SpaceProfile of the path from academic research to the Somin.AI ad-tech platform and its four modules.
Talk · 2023Under the Hood of Social Media Advertising: How Do We use AI Responsibly for Advertising Targeting and Creative EvaluationWSDM 2023 (ACM International Conference on Web Search and Data Mining), SingaporeConference talk on the technology behind ad targeting and creative scoring and on using it responsibly.
Talk · 2021Under the Boot of Google and Facebook and How to Crack it for better PerformanceODS AI GlobalHow machine learning drives Google and Facebook ad platforms, and techniques such as long-tail targeting to improve ad performance.
Lecture · 2020Lecture 1: Introduction (ITMO University, Social Media Computing)ITMO University course; Aleks Farseev (YouTube channel)Opening lecture of a university course on social media platforms, social media observatories and their challenges.
Lecture · 2017360 Degree User Profile Learning from Multiple Social Networks for Wellness and Urban Mobility Applications (Ph.D. defence public seminar)NUS School of ComputingPublic PhD defence on multi-source learning from social networks and sensors for demographic, wellness and venue-recommendation tasks.
Lecture · 2016 · in RussianПрофилирование атрибутов пользователей из множества источников данных различной модальности (Profiling user attributes from multiple multimodal data sources)Computer Science Club at POMI RAS; Лекториум (Lektorium)Russian-language lecture on inferring user attributes from many data sources of different modalities.
FAQ
SOMIN research FAQ
Is SOMIN built on real AI research?
Yes. SOMIN was co-founded by Prof. Aleks Farseev, and the models behind its audience personas, creative scoring and competitor analytics come from research he and the SOMIN team have published since 2015, including papers at AAAI, ACM Multimedia, SIGIR, WSDM and The Web Conference and in ACM Transactions on Information Systems.
Where has SOMIN research been published?
This page lists 28 peer-reviewed papers, demos and abstracts in venues including AAAI, ACM MM, ACM TIST, ACM TOIS, ICMR, SIGIR, WSDM, WWW. Each entry links to the publisher page or DOI, and to an open-access PDF where one exists.
Who builds SOMIN?
SOMIN is built by seasoned marketers and an AI professor. Prof. Aleks Farseev leads the research and the company; the SOMIN team combines machine-learning researchers, several of whom co-author the papers above, with marketers who work with brand and agency teams every day.
How does the research show up in the product?
Multi-source audience profiling powers SOMIN personas, personality-driven recommendation shapes persona-matched creative, creative-performance prediction scores concepts before launch, and explainable AI with large language models explains why competitor content works. Agentic AI research keeps generated content distinctive by grounding it in real category data.
Where can I watch talks about SOMIN?
Talks are listed above with links: an industry expert talk at ACM Multimedia 2025, a keynote at the Digital Marketing Conference Kuala Lumpur 2025, lectures at INSEAD and NUS, the ATxSG 2026 pitch and Marketing Mondays sessions on YouTube.
See the research run on your category
SOMIN reads your competitors, creators and audience, then hands you pre-scored ideas you can brief today.