谁在打造 SOMIN
资深营销人与一位 AI 教授，共同打造一款产品
Aleks Farseev 教授在新加坡国立大学攻读博士学位，研究同时从多个社交网络中学习用户画像，之后共同创立了 SOMIN。他是数字营销 AI 领域的研究教授，其在受众画像、个性驱动推荐和广告可解释 AI 方面的工作，在 Semantic Scholar 上被引用 577 次（截至 2026-10-17）。
除了研究团队，SOMIN 的营销人员还把这些模型转化为品牌和代理商团队每周都在使用的行动手册：营销空白点图谱、用户画像与消费者矛盾、预评分概念和内容日历。
研究者主页
引用数据来自 Semantic Scholar，2026-10-17。
从论文到产品
如今在 SOMIN 中运行的七条研究主线
下面的每一条研究主线，都对应平台中的一项能力。点击一篇论文，即可在出版方网站上阅读。
01
基于多种数据源的受众画像
如何同时利用多个网络上的帖子、图片、签到和传感器数据来了解受众是谁，以及数据来源为何会改变模型学到的内容。
- 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
02
个性驱动的内容
根据受众的内容推断其个性，并据此选择和生成该受众会有回应的帖子。
- 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
03
发布前为创意评分
根据广告创意的文案、图片、定向和设置预测其表现，并解释评分，让营销人员能够据此行动。
- 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
04
用于竞品分析的可解释 AI 与大语言模型
将效果模型与大语言模型结合，解读竞争对手的传播内容，并说明某个做法为什么有效，而不仅仅是它有效。
- 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
05
智能体 AI 与策略共创
在撰写之前先检索真实情境数据的智能体，让内容保持独特，而不是趋同于相同的泛泛输出。
- 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
06
创作者与达人分析
找到合适的创作者和账号，用更少的标注对社交帖子进行分类，并区分个人账号、品牌账号和名人账号。
- 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
出版物
顶级会议和期刊论文
发表于 AAAI、ACM Multimedia、SIGIR，以及 ACM TOIS 和 ACM TIST 的完整论文和期刊文章。
- ACM TOIS · 2025 · 期刊文章Fusing 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 · 完整论文Personality-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.开放获取 PDF
- AAAI · 2017 · 完整论文TweetFit: 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.开放获取 PDF
- SIGIR · 2017 · 完整论文Cross-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 · 期刊文章Tweet 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 · 期刊文章Learning 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.
顶级会议上的论文、演示和摘要
在 ACM Multimedia、AAAI、SIGIR、WSDM、The Web Conference、ICMR、CLEF 和 WebSci 上发表的论文、行业与演示论文以及学生摘要。
- SIGIR · 2026 · 论文SOMIN: 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 · 论文MindFuse: 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.开放获取 PDF
- WWW · 2025 · 配套论文SOEX: 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 · 行业演示SOMIN: 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 · 论文Against 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.开放获取 PDF
- WSDM · 2023 · 演示论文SoCraft: 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 · 演示论文"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 · 演示论文SoMin.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.开放获取 PDF
- AAAI · 2020 · 学生摘要I 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.开放获取 PDF
- AAAI · 2019 · 学生摘要A 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.开放获取 PDF
- ACM MM · 2018 · 论文SoMin.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 · 论文Multi-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 · 学生摘要Towards 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.开放获取 PDF
- ACM MM · 2016 · 演示论文bBridge: 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 · 完整论文Harvesting 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 · 论文Cross-Social Network Collaborative RecommendationAleksandr Farseev, Denis Kotkov, Alexander Semenov, Jari Veijalainen, Tat-Seng Chua. Proceedings of the ACM Web Science Conference (WebSci '15).
期刊、研讨会与预印本
- arXiv · 2024 · 预印本SOMONITOR: Combining Explainable AI & Large Language Models for Marketing AnalyticsAleksandr Farseev, Qi Yang, Marlo Ongpin, Ilia Gossoudarev, et al.. arXiv preprint arXiv:2407.13117（未经同行评审）。
- WSDM · 2023 · 演讲摘要Under 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（演讲摘要）。
- Frontiers in Big Data · 2022 · 期刊论文Do 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).开放获取 PDF
- ICMR workshop · 2021 · 研讨会论文Two-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).开放获取 PDF
- ACM MM workshop · 2021 · 研讨会论文Improving 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 · 论文Person, 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 · 文章360° user profiling: past, future, and applicationsAleksandr Farseev, Mohammad Akbari, Ivan Samborskii, Tat-Seng Chua. ACM SIGWEB Newsletter, 2016, pp. 1-11.
演讲与讲座
主题演讲、讲座与 Marketing Mondays 专场
Aleks Farseev 教授谈广告中的 AI，从 ACM Multimedia、INSEAD 到 Marketing Mondays。视频将在 YouTube 打开。
路演 · 2026From 6 Weeks to 13 Minutes: Pitching SOMIN AI at ATxSG 2026ATxSG 2026 (Asia Tech x Singapore)；Marketing Mondays by SOMIN
SOMIN 四大模块（竞品洞察、空白点发现、概念生成、上市前广告评分）的创业路演，并附 Mothercare 案例研究。
行业专家演讲 · 2025Will AI Make Agencies Obsolete? Rethinking the Future of AdvertisingACM Multimedia 2025，都柏林（Industry Expert Talk IET #2）；视频见 Marketing Mondays by SOMIN对比 AI 进入广告业的三种方式（取代、辅助和解释创意工作），以及广告代理商如何适应。
路演 · 2025SOMIN @madfestlondon 2025 - L'Oreal Brand Challenge CompetitionMAD//Fest London 2025；Marketing Mondays by SOMINSOMIN 参加 L'Oreal 品牌挑战赛的作品，主题为可规模化、由创作者主导的内容策略（视频发布于 2025-07-14）。
主题演讲 · 2025The Future of Generative AI in Marketing CommunicationsDigital Marketing Conference Kuala Lumpur 2025 (DMCKL2025)；Marketing Mondays by SOMIN关于生成式 AI 用于受众细分和营销活动搭建的主题演讲，并以 Miraflora Wagyu 案例研究结合 SOMONITOR 和 GWI 进行讲解。
讲座 · 2025INSEAD: How AI Cut Marketing Costs for a Beef BrandINSEAD 讲座；Marketing Mondays by SOMIN讲座介绍 AI 消费者洞察和竞品洞察如何帮助一家美国高端牛肉品牌降低获客成本。
讲座 · 2025NUS Engineering: Business Strategy with GA4, Meta Ads & SOMONITORNUS Engineering（商业工程专业学生）；Marketing Mondays by SOMIN课堂环节，涵盖 Google Analytics 4、Meta Ads Manager 以及使用 SOMONITOR 进行的竞品洞察。
Marketing Mondays · 2024Marketing Mondays: The Significance Of Responsible AI for Marketing Strategy & BeyondMarketing Mondays at Block71 Singapore；Marketing Mondays by SOMIN围炉谈话，探讨在营销中负责任地使用大语言模型，由 Aleks Farseev 教授在 Block71 Singapore 联合主持。
演讲 · 2024The Intelligent Advantage: Large Language Models Redefining Marketing Decision-MakingTechnology for Marketing（YouTube 频道）大语言模型如何加快竞品、用户画像、品牌语调和痛点分析，以及为什么它们应当辅助而非取代营销人员。
演示 · 2024SOMONITOR Demo - Travel Agents and Tourist Guides Industry Forum 2024Travel Agents and Tourist Guides Industry Forum 2024（Singapore Tourism Board）；SOMIN 频道面向旅游行业的 SOMONITOR 现场演示。
播客 · 2023 · 俄语«Нужно разобраться со скиллами, с головой, а потом уже деньги искать»（先把技能和思路理清楚，然后再去找钱）MTS StartUp Hub，播客《От сида до экзита》（从种子轮到退出）俄语访谈，谈及在海外打造 SoMin.ai、风险投资的低迷，以及大语言模型是否真的是增长机会。
演示 · 2023SoMin.ai Platform DemoAlex Farseev（YouTube 频道）SOADS（长尾广告定向）和 SOMONITOR（创意评分、SODA 大语言模型助手）模块的演示讲解。
演讲 · 2023From Academic Research to Adtech Entrepreneurship: The Journey of Aleks Farseev and Somin.AIDigital Ignition - A Coworking Space人物专访，讲述从学术研究到 Somin.AI 广告科技平台及其四大模块的历程。
演讲 · 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)，新加坡会议演讲，介绍广告定向和创意评分背后的技术，以及如何负责任地使用这些技术。
演讲 · 2021Under the Boot of Google and Facebook and How to Crack it for better PerformanceODS AI Global介绍机器学习如何驱动 Google 和 Facebook 广告平台，以及长尾定向等提升广告效果的技术。
讲座 · 2020Lecture 1: Introduction (ITMO University, Social Media Computing)ITMO University 课程；Aleks Farseev（YouTube 频道）一门大学课程的开篇讲座，介绍社交媒体平台、社交媒体观测站及其面临的挑战。
讲座 · 2017360 Degree User Profile Learning from Multiple Social Networks for Wellness and Urban Mobility Applications (Ph.D. defence public seminar)NUS School of Computing博士论文公开答辩，主题是从社交网络和传感器进行多源学习，用于人口特征、健康和场所推荐任务。
讲座 · 2016 · 俄语Профилирование атрибутов пользователей из множества источников данных различной модальности（从多种模态的多个数据源中分析用户属性）Computer Science Club at POMI RAS；Лекториум (Lektorium)俄语讲座，介绍如何从多种不同模态的数据源中推断用户属性。
FAQ
SOMIN 研究常见问题
SOMIN 是建立在真正的 AI 研究之上吗？
是的。SOMIN 由 Aleks Farseev 教授联合创办，其受众用户画像、创意评分和竞品分析背后的模型，均源自他与 SOMIN 团队自 2015 年以来发表的研究成果，包括 AAAI、ACM Multimedia、SIGIR、WSDM 和 The Web Conference 的论文，以及发表于 ACM Transactions on Information Systems 的论文。
SOMIN 的研究发表在哪里？
本页列出 28 篇经同行评审的论文、演示和摘要，发表于 AAAI、ACM MM、ACM TIST、ACM TOIS、ICMR、SIGIR、WSDM、WWW 等会议和期刊。每个条目都链接到出版方页面或 DOI，如有开放获取 PDF 也一并提供。
谁在打造 SOMIN？
SOMIN 由经验丰富的营销人和一位 AI 教授打造。Aleks Farseev 教授负责研究工作并领导公司；SOMIN 团队既有机器学习研究人员（其中数位是上述论文的合著者），也有每天与品牌和代理商团队合作的营销人员。
这些研究如何体现在产品中？
多源受众画像分析支撑 SOMIN 的用户画像，性格驱动的推荐塑造与用户画像相匹配的创意，创意效果预测在发布前为概念评分，而可解释 AI 与大语言模型的结合则解释竞品内容为何有效。智能体 AI 研究通过以真实品类数据为依据，使生成的内容保持独特。
在哪里可以观看关于 SOMIN 的演讲？
上方列出了带链接的演讲：ACM Multimedia 2025 的行业专家演讲、Digital Marketing Conference Kuala Lumpur 2025 的主题演讲、INSEAD 和 NUS 的讲座、ATxSG 2026 的路演，以及 YouTube 上的 Marketing Mondays 专场。