“Down the Rabbit Hole” of Vaccine Misinformation on YouTube: Network Exposure Study

Background Social media platforms such as YouTube are hotbeds for the spread of misinformation about vaccines. Objective The aim of this study was to explore how individuals are exposed to antivaccine misinformation on YouTube based on whether they start their viewing from a keyword-based search or from antivaccine seed videos. Methods Four networks of videos based on YouTube recommendations were collected in November 2019. Two search networks were created from provaccine and antivaccine keywords to resemble goal-oriented browsing. Two seed networks were constructed from conspiracy and antivaccine expert seed videos to resemble direct navigation. Video contents and network structures were analyzed using the network exposure model. Results Viewers are more likely to encounter antivaccine videos through direct navigation starting from an antivaccine video than through goal-oriented browsing. In the two seed networks, provaccine videos, antivaccine videos, and videos containing health misinformation were all found to be more likely to lead to more antivaccine videos. Conclusions YouTube has boosted the search rankings of provaccine videos to combat the influence of antivaccine information. However, when viewers are directed to antivaccine videos on YouTube from another site, the recommendation algorithm is still likely to expose them to additional antivaccine information.

“Down the Rabbit Hole” of Vaccine Misinformation on YouTube: Network Exposure Study (Preprint)

BACKGROUND Social media platforms such as YouTube are hotbeds for the spread of misinformation about vaccines. OBJECTIVE The aim of this study was to explore how individuals are exposed to antivaccine misinformation on YouTube based on whether they start their viewing from a keyword-based search or from antivaccine seed videos. METHODS Four networks of videos based on YouTube recommendations were collected in November 2019. Two search networks were created from provaccine and antivaccine keywords to resemble <i>goal-oriented browsing</i>. Two seed networks were constructed from conspiracy and antivaccine expert seed videos to resemble <i>direct navigation</i>. Video contents and network structures were analyzed using the network exposure model. RESULTS Viewers are more likely to encounter antivaccine videos through direct navigation starting from an antivaccine video than through goal-oriented browsing. In the two seed networks, provaccine videos, antivaccine videos, and videos containing health misinformation were all found to be more likely to lead to more antivaccine videos. CONCLUSIONS YouTube has boosted the search rankings of provaccine videos to combat the influence of antivaccine information. However, when viewers are directed to antivaccine videos on YouTube from another site, the recommendation algorithm is still likely to expose them to additional antivaccine information.

A typology of job search sources: Exploring the changing nature of job search networks

This study explored American job seekers’ network of information sources using a random sample. Results revealed a pattern that job seekers segmented information sources by social (i.e. personal and professional acquaintances, family, and friends), formal (i.e. employment agencies, printed advertisements, and career events), and online (i.e. online pages and social network sites) types. Although online sources were particularly central in the network, job seekers who used one source type did so at the expense of other types of sources. Older and poorer job seekers were more likely to use formal sources, while online sources were used more by job seekers with higher education and Internet efficacy. The discussion offers advice for job seekers and those who coach job search. This study extends strength of weak ties theory by demonstrating the importance of online sources in job search.

Quantification of PM_2.5 organic carbon sampling artifacts in US networks

Field blanks (bQF) and backup filters (quartz-fiber behind quartz-fiber filter; QBQ) have been adopted by US long-term air quality monitoring networks to estimate PM2.5 organic carbon (OC) sampling artifacts. This study documents bQF and QBQ carbon levels for the: 1) Interagency Monitoring of Protected Visual Environments (IMPROVE); 2) Speciation Trends Network (STN; part of the Chemical Speciation Network [CSN]); and 3) Southeastern Aerosol Research and Characterization (SEARCH) networks and examines the similarities/differences associated with network-specific sampling protocols. A higher IMPROVE sample volume and smaller filter deposit area results in PM2.5 areal density (μg/cm2 on filter) 3–11 times those of STN/CSN and SEARCH samples for the same ambient PM2.5 concentrations, thus reducing the relative contribution of sampling artifacts from passive OC adsorption. A relatively short (1–15 min) passive exposure period of STN/CSN and SEARCH bQF OC (0.8–1 μg/cm2) underestimates positive and negative OC artifacts resulting from passive adsorption or evaporation of semi-volatile organic compounds on quartz-fiber filters. This is supported by low STN/CSN and SEARCH bQF levels and lack of temporal or spatial variability among the sites within the networks. With a much longer period, ~7 days of ambient passive exposure, average IMPROVE bQF and QBQ OC are comparable (2.4±0.5 and 3.1±0.8 μg/cm2, respectively) and more than twice levels found in the STN/CSN and SEARCH networks. Sampling artifacts in STN/CSN were estimated from collocated IMPROVE samples based on linear regression. At six of the eight collocated sites in this study, STN/CSN bQFs underestimated OC artifacts by 11–34%. Using a preceding organic denuder in the SEARCH network minimized passive adsorption on QBQ, but OC on QBQ may not be attributed entirely to the negative sampling artifact (e.g., evaporated or volatilized OC from the front filter deposits after sample collection).

Quantification of organic carbon sampling artifacts in US non-urban and urban networks

Different approaches to estimate organic sampling artifacts have been adopted by US long-term air quality monitoring networks. This study documents field blank (bQF) and backup filter (quartz-fiber behind quartz-fiber filter; QBQ) carbon levels for the: 1) Interagency Monitoring of Protected Visual Environments (IMPROVE); 2) Speciation Trends Network (STN; part of the Chemical Speciation Network [CSN]; and 3) Southeastern Aerosol Research and Characterization (SEARCH) networks. Filter pack sample handling procedures and blank correction methods are examined. Due to a relatively short (1–15 min) passive exposure period, STN/CSN and SEARCH network bQF organic carbon (OC; 0.8–1 μg/cm2) may underestimate positive and negative OC artifacts, respectively, resulting from passive adsorption or volatilization of volatile or semi-volatile organic compounds on quartz-fiber filters while they are in the sampler. This is evidenced by a lack of temporal or spatial variability and low bQF levels. With ~7 d of ambient passive exposure, average IMPROVE bQF and QBQ OC are comparable (2.4±0.5 and 3.1±0.8 μg/cm2) and more than twice those found in the STN/CSN and SEARCH networks. Lower STN/CSN flow rates and larger filter deposit areas result in 9–20% of the areal density (μg/cm2) compared to IMPROVE areal deposits. STN/CSN bQF values are 11–34% lower than linear regression intercepts derived from collocated IMPROVE-STN/CSN data pairs. Using a preceding organic denuder in the SEARCH network reduces the organic vapor adsorption on QBQ, though the longer QBQ period in the sampler may result from passive organic vapor adsorption as well as evaporated OC from the front filter deposits.