Twitter’s role in the fight against HIV
Twitter is not only a platform to learn information, have interaction with like-minded people, launch insults or give reward. It is also a far-reaching and revealing digital "petri dish" to review human conduct that will assist predict illness outbreaks, like HIV, and inform public well being efforts, as a number of research and social media consultants have proven over the previous few years. These 140 character tweets, and never simply those about well being, have been a treasure chest for epidemiologists, laptop scientists, psychologists, and plenty of others to dig by way of.
"Twitter is a compendium of who we're," stated H. Andrew Schwartz, PhD, a visiting assistant professor of Pc and Info Science on the College of Pennsylvania and Penn Medication's Social Media and Well being Innovation Lab. "The language that we write is a illustration of our every day lives. It captures points of individuals which might be in any other case fairly elusive to well being researchers, such because the psychological aspect that is troublesome to get at."
It is these points that may be missed with conventional -- and gradual to publish -- illness surveillance, research, and surveys. Tapping into the massive information of Twitter has helped higher forecast flu outbreaks and bronchial asthma assaults, analysis has proven. "This runny nostril will not cease!" and the hashtag "#wheezing" may be very telling.
Tweets like this even have the potential to identify total well being tendencies that would inform campaigns and interventions to assist deal with folks with a slew of ailments, Penn researchers mentioned in an October 2015 examine that included Schwartz and senior creator, Raina M. Service provider, MD, MSHP, director of the Social Media and Well being Innovation Lab. The less-obvious tweets are giving Penn researchers higher perception into well being, too. An evaluation over 150 million tweets revealed helpful data about HIV in communities throughout the US and the individuals who stay in them.
Motion tweets -- ones written with phrases like "go," act," "work," "have interaction" -- have been considerably extra prone to be coming from folks residing in counties with decrease HIV charges in comparison with folks residing in counties with greater HIV charges, Schwartz and his colleagues reported within the journal AIDS and Conduct final yr. Authors of examine additionally included Lyle Ungar, PhD, a professor of Pc Science at Penn, and Dolores Albarracín, PhD, a former professor of Communication and Psychology at Penn who's at the moment on college on the College of Illinois at Urbana-Champaign.
These weren't "I'm HIV constructive" or "I'll get examined" sort of tweets, which previous research have tracked. It was extra about normal objectives or representations, "I plan on…" or "I will beat you at…," for instance. Utilizing a dictionary of 854 phrases for his or her evaluation, the staff got down to reply whether or not one of these language corresponded with HIV circumstances.
Within the well being area, these motion tweets have been linked to elevated bodily exercise, however the way it performed out within the HIV area was unclear. Being in an lively group surroundings, the authors stated, could promote faster analysis and remedy of HIV -- which may finally assist scale back the transmission and prevalence of the illness.
The tweets may have gone other ways: in direction of extra constructive well being selections or to dangerous conduct that will enhance an individual's probability of contracting the illness. The previous was true on this case, and because the authors described, was critically informative, with the "the potential to be extremely transformative for prevention and surveillance practices."
At the moment, outcomes of large-scale surveys figuring out particular person and group threat elements for HIV and different infectious ailments can take years to point out up, so having a real-time take a look at the conversations taking place on Twitter may show to be very advantageous, Albarracín, Ungar, and their colleagues talk about on their Well being and Social Media Group web page. "To fight HIV successfully," they wrote, "we have to know the place remedy sources have to be geared toward and the place new well being dangers are creating." In different phrases, information is commonly too late to behave upon.
With Twitter and complex geocoding methods, public well being researchers can doubtlessly estimate the present HIV threat of particular areas and implement preventive measures earlier than the precise outbreak happens, the authors of the AIDS and Conduct examine stated.
"Such a information can inform public well being interventions," stated Schwartz, who can also be an assistant professor of Pc Science at Stony Brook College. "With this data, you should utilize a rating of how motion oriented a group is and the place you might wish to intervene, and begin some packages about HIV consciousness."
This large information method stems past HIV. Schwartz and his colleagues examine a number of different ailments, resembling diabetes, to see what the predictive capabilities and associations of Twitter can reveal. Apparently, preliminary outcomes present a hyperlink between the phrase "church" on social media and better charges of diabetes, he stated. The complete outcomes are anticipated to be revealed this yr.
It is all a part of the continued work with "pure language processing" from the social media lab at Penn, in addition to Stony Brook and the College of Illinois -- every of which contains a multidisciplinary staff of researchers with backgrounds in medication, regulation, laptop science, demography, geographic data techniques, biostatistics, well being coverage, communications, advertising, design, behavioral well being, and operations administration.
"Fb and Twitter opens up the power to look throughout open vocabulary, unanticipated language patterns posted 'within the wild'," Schwartz stated. "We're taking a look at many ailments and what the connections with language are -- which of them can we predict effectively and which of them can we not."
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It is these points that may be missed with conventional -- and gradual to publish -- illness surveillance, research, and surveys. Tapping into the massive information of Twitter has helped higher forecast flu outbreaks and bronchial asthma assaults, analysis has proven. "This runny nostril will not cease!" and the hashtag "#wheezing" may be very telling.
Tweets like this even have the potential to identify total well being tendencies that would inform campaigns and interventions to assist deal with folks with a slew of ailments, Penn researchers mentioned in an October 2015 examine that included Schwartz and senior creator, Raina M. Service provider, MD, MSHP, director of the Social Media and Well being Innovation Lab. The less-obvious tweets are giving Penn researchers higher perception into well being, too. An evaluation over 150 million tweets revealed helpful data about HIV in communities throughout the US and the individuals who stay in them.
Motion tweets -- ones written with phrases like "go," act," "work," "have interaction" -- have been considerably extra prone to be coming from folks residing in counties with decrease HIV charges in comparison with folks residing in counties with greater HIV charges, Schwartz and his colleagues reported within the journal AIDS and Conduct final yr. Authors of examine additionally included Lyle Ungar, PhD, a professor of Pc Science at Penn, and Dolores Albarracín, PhD, a former professor of Communication and Psychology at Penn who's at the moment on college on the College of Illinois at Urbana-Champaign.
These weren't "I'm HIV constructive" or "I'll get examined" sort of tweets, which previous research have tracked. It was extra about normal objectives or representations, "I plan on…" or "I will beat you at…," for instance. Utilizing a dictionary of 854 phrases for his or her evaluation, the staff got down to reply whether or not one of these language corresponded with HIV circumstances.
Within the well being area, these motion tweets have been linked to elevated bodily exercise, however the way it performed out within the HIV area was unclear. Being in an lively group surroundings, the authors stated, could promote faster analysis and remedy of HIV -- which may finally assist scale back the transmission and prevalence of the illness.
The tweets may have gone other ways: in direction of extra constructive well being selections or to dangerous conduct that will enhance an individual's probability of contracting the illness. The previous was true on this case, and because the authors described, was critically informative, with the "the potential to be extremely transformative for prevention and surveillance practices."
At the moment, outcomes of large-scale surveys figuring out particular person and group threat elements for HIV and different infectious ailments can take years to point out up, so having a real-time take a look at the conversations taking place on Twitter may show to be very advantageous, Albarracín, Ungar, and their colleagues talk about on their Well being and Social Media Group web page. "To fight HIV successfully," they wrote, "we have to know the place remedy sources have to be geared toward and the place new well being dangers are creating." In different phrases, information is commonly too late to behave upon.
With Twitter and complex geocoding methods, public well being researchers can doubtlessly estimate the present HIV threat of particular areas and implement preventive measures earlier than the precise outbreak happens, the authors of the AIDS and Conduct examine stated.
"Such a information can inform public well being interventions," stated Schwartz, who can also be an assistant professor of Pc Science at Stony Brook College. "With this data, you should utilize a rating of how motion oriented a group is and the place you might wish to intervene, and begin some packages about HIV consciousness."
This large information method stems past HIV. Schwartz and his colleagues examine a number of different ailments, resembling diabetes, to see what the predictive capabilities and associations of Twitter can reveal. Apparently, preliminary outcomes present a hyperlink between the phrase "church" on social media and better charges of diabetes, he stated. The complete outcomes are anticipated to be revealed this yr.
It is all a part of the continued work with "pure language processing" from the social media lab at Penn, in addition to Stony Brook and the College of Illinois -- every of which contains a multidisciplinary staff of researchers with backgrounds in medication, regulation, laptop science, demography, geographic data techniques, biostatistics, well being coverage, communications, advertising, design, behavioral well being, and operations administration.
"Fb and Twitter opens up the power to look throughout open vocabulary, unanticipated language patterns posted 'within the wild'," Schwartz stated. "We're taking a look at many ailments and what the connections with language are -- which of them can we predict effectively and which of them can we not."
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