Publication

On the ground validation of online diagnosis with Twitter and medical records

Marcel Salathé
2014
Conference paper

Abstract

Social media has been considered as a data source for tracking disease. However, most analyses are based on models that prioritize strong correlation with population-level disease rates over determining whether or not specific individual users are actually sick. Taking a different approach, we develop a novel system for social-media based disease detection at the individual level using a sample of professionally diagnosed individuals. Specifically, we develop a system for making an accurate influenza diagnosis based on an individual's publicly available Twitter data. We find that about half (17/35 = 48.57%) of the users in our sample that were sick explicitly discuss their disease on Twitter. By developing a meta classifier that combines text analysis, anomaly detection, and social network analysis, we are able to diagnose an individual with greater than 99% accuracy even if she does not discuss her health

Official source

https://infoscience.epfl.ch/record/214477?ln=en

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Related concepts (37)

Disease

A disease is a particular abnormal condition that negatively affects the structure or function of all or part of an organism and is not immediately due to any external injury. Diseases are often known to be medical conditions that are associated with specific signs and symptoms. A disease may be caused by external factors such as pathogens or by internal dysfunctions. For example, internal dysfunctions of the immune system can produce a variety of different diseases, including various forms of immunodeficiency, hypersensitivity, allergies, and autoimmune disorders.

Social network analysis

Social network analysis (SNA) is the process of investigating social structures through the use of networks and graph theory. It characterizes networked structures in terms of nodes (individual actors, people, or things within the network) and the ties, edges, or links (relationships or interactions) that connect them. Examples of social structures commonly visualized through social network analysis include social media networks, meme spread, information circulation, friendship and acquaintance networks, peer learner networks, business networks, knowledge networks, difficult working relationships, collaboration graphs, kinship, disease transmission, and sexual relationships.

Lyme disease

Lyme disease, also known as Lyme borreliosis, is a vector-borne disease caused by Borrelia bacteria, which are spread by ticks in the genus Ixodes. The most common sign of infection is an expanding red rash, known as erythema migrans (EM), which appears at the site of the tick bite about a week afterwards. The rash is typically neither itchy nor painful. Approximately 70–80% of infected people develop a rash. Early diagnosis can be difficult. Other early symptoms may include fever, headaches and tiredness.

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