Short-term Internet search using makes people rely on search engines when facing unknown issues

The "multiple exposure effect" (MEE): How multiple exposures to similarly biased online content can cause increasingly larger shifts in opinions and voting preferences

In three randomized, controlled experiments performed on simulations of three popular online platforms - Google search, X/Twitter, and Alexa - with a total of 1,488 undecided, eligible US voters, we asked whether multiple exposures to similarly biased content on those platforms could shift opinions and voting preferences more than a single exposure could. All participants were first shown brief biographies of two political candidates, then asked about their voting preferences, then exposed to biased content on one of our three simulated platforms, and then asked again about their voting preferences. In all experiments, participants in different groups saw biased content favoring one candidate, his or her opponent, or neither. In all the experiments, our primary dependent variable was Vote Manipulation Power (VMP), the percentage increase in the number of participants inclined to vote for one candidate after having viewed content favoring that candidate. In Experiment 1 (on our Google simulator), the VMP increased with successive searches from 14.3% to 20.2% to 22.6%. In Experiment 2 (on our X/Twitter simulator), the VMP increased with successive exposures to biased tweets from 49.7% to 61.8% to 69.1%. In Experiment 3 (on our Alexa simulator), the VMP increased with successive exposures to biased replies from 72.1% to 91.2% to 98.6%. Corresponding shifts were also generally found for how much participants reported liking and trusting the candidates and for participants' overall impression of the candidates. Because multiple exposures to similarly biased content might be common on the internet, we conclude that our previous reports about the possible impact of biased content - always based on single exposures - might have underestimated its possible impact. Findings in our new experiments exemplify what we call the "multiple exposure effect" (MEE).

Google effects on memory: a meta-analytical review of the media effects of intensive Internet search behavior

People are increasingly using the web for fact-checking and other forms of information seeking. The "Google effects" refers to the idea that individuals rely on the Internet as a source of knowledge rather than remembering it for themselves. However, few literature review have yet comprehensively examined the media effects of this intensive Internet search behavior. In this study, by carrying out meta-analysis, we found that google effects is closely associated with cognitive load, behavioral phenotype and cognitive self-esteem. And this phenomenon is also more likely to happen while using a mobile phone to browse the Internet rather than a computer. People with a larger knowledge base are less susceptible to the consequences of Internet use than those with a smaller knowledge base. The media effect was stronger for persons who had used the Internet before than for those who had not. And meta-analyses show that participants in North America (parameter = -1.0365, 95%CI = [-1.8758, -0.1972], p < 0.05) are more susceptible to frequent Internet search behavior relative to other regions. Overall, google effects on memory challenges the way individuals seek and read information, and it may lead to changes in cognitive and memory mechanisms.

Time-Series Associations between Public Interest in COVID-19 Variants and National Vaccination Rate: A Google Trends Analysis

The emergence of a constantly mutating novel virus has led to considerable public anxiety amid the COVID-19 pandemic. Information seeking is a common strategy to cope with pandemic anxiety. Using Google Trends analysis, this study investigated public interest in COVID-19 variants and its temporal associations with the disease-prevention measure of vaccination during the initial COVID-19 vaccine rollout period (13 December 2020 to 25 September 2021). Public interest was operationalized as the relative search volume of online queries of variant-related terms in the countries first affected by the Alpha, Beta, and Delta variants: the UK, South Africa, and India, respectively. The results show that public interest in COVID-19 variants was greater during the Delta-variant-predominant period than before this period. The time-series cross-correlation analysis revealed positive temporal associations (i.e., greater such public interest was accompanied by an increase in national vaccination rate) tended to occur more frequently and at earlier time lags than the negative temporal associations. This study yielded new findings regarding the temporal changes in public interest in COVID-19 variants, and the between-country variations in these public interest changes can be explained by differences in the rate and pace of vaccination among the countries of interest.

The Answer Bot Effect (ABE): A powerful new form of influence made possible by intelligent personal assistants and search engines

We introduce and quantify a relatively new form of influence: the Answer Bot Effect (ABE). In a 2015 report in PNAS, researchers demonstrated the power that biased search results have to shift opinions and voting preferences without people’s knowledge–by up to 80% in some demographic groups. They labeled this phenomenon the Search Engine Manipulation Effect (SEME), speculating that its power derives from the high level of trust people have in algorithmically-generated content. We now describe three experiments with a total of 1,736 US participants conducted to determine to what extent giving users “the answer”–either via an answer box at the top of a page of search results or via a vocal reply to a question posed to an intelligent personal assistant (IPA)–might also impact opinions and votes. Participants were first given basic information about two candidates running for prime minister of Australia (this, in order to assure that participants were “undecided”), then asked questions about their voting preferences, then given answers to questions they posed about the candidates–either with answer boxes or with vocal answers on an Alexa simulator–and then asked again about their voting preferences. The experiments were controlled, randomized, double-blind, and counterbalanced. Experiments 1 and 2 demonstrated that answer boxes can shift voting preferences by as much as 38.6% and that the appearance of an answer box can reduce search times and clicks on search results. Experiment 3 demonstrated that even a single question-and-answer interaction on an IPA can shift voting preferences by more than 40%. Multiple questions posed to an IPA leading to answers that all have the same bias can shift voting preferences by more than 65%. Simple masking procedures still produced large opinion shifts while reducing awareness of bias to close to zero. ABE poses a serious threat to both democracy and human autonomy because (a) it produces large shifts in opinions and voting preferences with little or no user awareness, (b) it is an ephemeral form of influence that leaves no paper trail, and (c) worldwide, it is controlled almost exclusively by just four American tech companies. ABE will become a greater threat as people increasingly rely on IPAs for answers.

Exploring the Impact of Internet Use on Memory and Attention Processes

The rapid uptake of the internet has provided a new platform for people to engage with almost all aspects of life. As such, it is currently crucial to investigate the relationship between the internet and cognition across contexts and the underlying neurobiological mechanisms driving this. We describe the current understanding of this relationship across the literature and outline the state of knowledge surrounding the potential neurobiological drivers. Through focusing on two key areas of the nascent but growing literature, first the individual- and population-level implications for attention processes and second the neurobiological drivers underpinning internet usage and memory, we describe the implications of the internet for cognition, assess the potential mechanisms linking brain structure to cognition, and elucidate how these influence behaviour. Finally, we identify areas that now require investigation, including (i) the importance of the variation in individual levels of internet usage, (ii) potential individual behavioural implications and emerging population-level effects, and the (iii) interplay between age and the internet–brain relationships across the stages of development.

More stringent criteria are needed for diagnosing internet gaming disorder: Evidence from regional brain features and whole-brain functional connectivity multivariate pattern analyses

BACKGROUND

Internet gaming disorder (IGD) is included in the DSM-5 as a provisional diagnosis. Whether IGD should be regarded as a disorder and, if so, how it should be defined and thresholded have generated considerable debate.

METHODS

In the current study, machine learning was used, based on regional and interregional brain features. Resting-state data from 374 subjects (including 148 IGD subjects with DSM-5 scores ≥5 and 93 IGD subjects with DSM-5 scores ≥6) were collected, and multivariate pattern analysis (MVPA) was employed to classify IGD from recreational game use (RGU) subjects based on regional brain features (ReHo) and communication between brain regions (functional connectivity; FC). Permutation tests were used to assess classifier performance.

RESULTS

The results demonstrated that when using DSM-5 scores ≥5 as the inclusion criteria for IGD subjects, MVPA could not differentiate IGD subjects from RGU, whether based on ReHo or FC features or by using different templates. MVPA could differentiate IGD subjects from RGU better than expected by chance when using DSM-5 scores ≥6 with both ReHo and FC features. The brain regions involved in the default mode network and executive control network and the cerebellum exhibited high discriminative power during classification.

DISCUSSION

The current findings challenge the current IGD diagnostic criteria thresholding proposed in the DSM-5, suggesting that more stringent criteria may be needed for diagnosing IGD. The findings suggest that brain regions involved in the default mode network and executive control network relate importantly to the core criteria for IGD.

More stringent criteria are needed for diagnosing internet gaming disorder: Evidence from regional brain features and whole-brain functional connectivity multivariate pattern analyses

BACKGROUND

Internet gaming disorder (IGD) is included in the DSM-5 as a provisional diagnosis. Whether IGD should be regarded as a disorder and, if so, how it should be defined and thresholded have generated considerable debate.

METHODS

In the current study, machine learning was used, based on regional and interregional brain features. Resting-state data from 374 subjects (including 148 IGD subjects with DSM-5 scores ≥5 and 93 IGD subjects with DSM-5 scores ≥6) were collected, and multivariate pattern analysis (MVPA) was employed to classify IGD from recreational game use (RGU) subjects based on regional brain features (ReHo) and communication between brain regions (functional connectivity; FC). Permutation tests were used to assess classifier performance.

RESULTS

The results demonstrated that when using DSM-5 scores ≥5 as the inclusion criteria for IGD subjects, MVPA could not differentiate IGD subjects from RGU, whether based on ReHo or FC features or by using different templates. MVPA could differentiate IGD subjects from RGU better than expected by chance when using DSM-5 scores ≥6 with both ReHo and FC features. The brain regions involved in the default mode network and executive control network and the cerebellum exhibited high discriminative power during classification.

DISCUSSION

The current findings challenge the current IGD diagnostic criteria thresholding proposed in the DSM-5, suggesting that more stringent criteria may be needed for diagnosing IGD. The findings suggest that brain regions involved in the default mode network and executive control network relate importantly to the core criteria for IGD.

The "online brain": how the Internet may be changing our cognition

The impact of the Internet across multiple aspects of modern society is clear. However, the influence that it may have on our brain structure and functioning remains a central topic of investigation. Here we draw on recent psychological, psychiatric and neuroimaging findings to examine several key hypotheses on how the Internet may be changing our cognition. Specifically, we explore how unique features of the online world may be influencing: a) attentional capacities, as the constantly evolving stream of online information encourages our divided attention across multiple media sources, at the expense of sustained concentration; b) memory processes, as this vast and ubiquitous source of online information begins to shift the way we retrieve, store, and even value knowledge; and c) social cognition, as the ability for online social settings to resemble and evoke real-world social processes creates a new interplay between the Internet and our social lives, including our self-concepts and self-esteem. Overall, the available evidence indicates that the Internet can produce both acute and sustained alterations in each of these areas of cognition, which may be reflected in changes in the brain. However, an emerging priority for future research is to determine the effects of extensive online media usage on cognitive development in youth, and examine how this may differ from cognitive outcomes and brain impact of uses of Internet in the elderly. We conclude by proposing how Internet research could be integrated into broader research settings to study how this unprecedented new facet of society can affect our cognition and the brain across the life course.

Internet Search Alters Intra- and Inter-regional Synchronization in the Temporal Gyrus

Internet search changed the way we store and recall information and possibly altered our brain functions. Previous studies suggested that Internet search facilitates the information-acquisition process. However, this process may cause individuals to lose the ability to store and recollect specific contents. Despite the numerous behavioral studies conducted in this field, little is known about the neural mechanisms underlying Internet searches. The present study explores potential brain activity changes induced by Internet search. The whole paradigm includes three phases, namely, pre-resting state fMRI (rs-fMRI) scan, 6-day Internet search training, and post rs-fMRI scan. We detected the functional integrations induced by Internet search training by comparing post- with pre-scan. Regional homogeneity (ReHo) and functional connectivity (FC) were used to detect intra- and interregional synchronized activity in 42 university students. Compared with pre-scan, post-scan showed decreased ReHo in the temporal gyrus, the middle frontal gyrus, and the postcentral gyrus. Further seed-based FC analysis showed that the temporal gyrus exhibited decreased FC in the parahippocampal cortex and the temporal gyrus after training. Based on the features of current task and functions exhibited by these brain regions, results indicate that short-term Internet search training changed the brain regional activities involved in memory retrieval. In general, this study provides evidence that supports the idea that Internet search can affect our brain functions.

Short-Term Internet-Search Training Is Associated with Increased Fractional Anisotropy in the Superior Longitudinal Fasciculus in the Parietal Lobe

The Internet search engine has become an indispensable tool for many people, yet the ways in which Internet searching may alter brain structure and function is poorly understood. In this study, we investigated the influence of short-term Internet-search “training” on white matter microstructure using diffusion tensor imaging (DTI). Fifty-nine valid subjects (Experimental group, 43; Control group, 16) completed the whole procedure: pre- DTI scan, 6-day's training and post- DTI scan. Using track-based spatial statistics, we found increased fractional anisotropy in the right superior longitudinal fasciculus at post-test as compared to pre-test in experimental group. Within the identified region of the right superior longitudinal fasciculus, decreased radial diffusivity (RD), and unchanged axial diffusivity (AD) were observed. These results suggest that short-term Internet-search training may increase white-matter integrity in the right superior longitudinal fasciculus. A possible mechanism for the observed FA change may involve increased myelination after training, although this possibility warrants additional investigation.