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Research area: Social sciences

Social sciences

Exploring how people use computing in their daily lives and the way people work, play, and connect with each other.

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1,091 results found
Publication

How visualizing inferential uncertainty can mislead readers about treatment effects in scientific results 

by Jake Hofman, Dan Goldstein, Jessica Hullman

Scientists presenting experimental results often choose to display either inferential uncertainty (e.g., uncertainty in the estimate of a population mean) or outcome uncertainty (e.g., variation of outcomes around that mean). How does this choice impact readers’ beliefs about the size of treatment effects? We investigate this question in two experiments comparing 95% confidence intervals (means and standard errors) to 95% prediction intervals (means and standard deviations). The first experiment finds that participants are willing to…

Publication

Adaptive Greedy versus Non-adaptive Greedy for Influence Maximization 

by Wei Chen; et. al.

We consider the adaptive influence maximization problem: given a network and a budget k, iteratively select k seeds in the network to maximize the expected number of adopters. In the full-adoption feedback model, after selecting each seed, the seed-picker observes all the resulting adoptions. In the myopic feedback model, the seed-picker only observes whether each neighbor of the chosen seed adopts. Motivated by the extreme success of greedy-based algorithms/heuristics for influence maximization, we propose the…

Publication

Gradient Method for Continuous Influence Maximization with Budget-Saving Considerations 

by Wei Chen, Weizhong Zhang, Haoyu Zhao

Continuous influence maximization (CIM) generalizes the original influence maximization by  incorporating general marketing strategies: a marketing strategy mix is a vector x = (x_1, … ,x_d) such that for each node v in a social network,  v could be activated as a seed of diffusion with probability h_v(x),  where h_v is a strategy activation function satisfying DR-submodularity. CIM is the task of selecting a strategy mix x with constraint x_1+ … + x_d <= k…

Publication

Influence Maximization with Spontaneous User Adoption 

by Lichao Sun; et. al.

We incorporate the realistic scenario of spontaneous user adoption into influence propagation (also refer to as self-activation) and propose the self-activation independent cascade (SAIC) model: nodes may be self activated besides being selected as seeds, and influence propagates from both selected seeds and self activated nodes. Self activation occurs in many real world situations; for example, people naturally share product recommendations with their friends, even without marketing intervention. Under the SAIC model, we study three…

Event

Swiss Joint Research Center Workshop 2020 

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The 7th annual workshop of the Microsoft-Swiss Joint Research Centre (with ETH Zurich/EPFL) takes place January 29-30, 2020 at EPFL in Lausanne. The workshop will provide an opportunity for project updates and collaborative meetings across twelve projects. Speakers from each project collaboration will present the current state of their projects and outlined future plans.

Bali project graphic - orange figure in blue circle
Project

Bali 

Bali is paving the path for a personal data ecosystem in which users are in control and can benefit from their data. Like a vault, Bali enables users to aggregate their information securely and privately and use it for their own benefit.

Career Opportunity

Research Intern – Causal Inference 

This internship project aims to improve modeling of user and advertiser behaviors through causal reasoning counterfactual methods. Interns should expect to combine information learned from observational studies with carefully designed A/B experiments to build robust, causal models of behaviors under intervention. The project area is a collaboration between Bing Ads and MSR AI’s IDEAS group. Data scientists in Bing Ads are focused on cutting edge machine learning and experimentation technologies. The IDEAS group brings together…

Career Opportunity

Internship Opportunities: User Experience/HCI Research 

We have an exciting opportunity for a User Experience/HCI Research intern to work with us at Microsoft Research Cambridge. Our project is a partnership with a Microsoft product team, exploring frontline-centric business processes in real-world organizations. Frontline workers are critical for how organizations create value. They are at the centre of our largest industries, such as healthcare, retail, and manufacturing; they include shop floor workers, production operators, sales associates, flight crew and many others. Focusing…

Career Opportunity

Research Intern – Political Economy 

The Microsoft Office of the Chief Technology Officer Pluralistic Organization for Dignity (OCTOPOD) group aims to help Microsoft envision, build and communicate a future for technology that affirms and empowers human creativity, communication and collaboration. Microsoft’s mission “to empower every person and every organization on the planet to achieve more” is only achievable if technology is advancing towards a future full of diverse human organization and focused on such empowerment. Yet today the dominant vision…

Career Opportunity

Research Intern – Conversation Speech Recognition 

Are you interested in AI and machine learning technology, especially involving speech and language? As one of Microsoft’s most exciting AI initiatives, speech recognition (SR) is driving the accuracy and robustness of natural user interfaces with natural spoken language and their deep integration to user-facing produce/service from Microsoft 1st party or 3rd party application. The Speech Group develops speech recognition features in Enterprise, Entertainment, and Desktop and Mobile products and particularly in the voice platform…

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