A Citizen Science Tool for Big-Data on Ghostly Episodes @TheSSEChannel
A Citizen Science Tool for Big-Data on Ghostly Episodes  @TheSSEChannel
Uploaded May 2022 | Updated September 2026, 17 hours ago
Introduction: Instrumentation has been used inconsistently in studies of “ghostly episodes“ (Houran & Lange, 1998; Dagnall et al., 2020). Moreover, big data analytics are likely needed to describe the important interactions among attitudinal, normative, and environmental variables that likely mediate percipients’ reports. The growth of social, mobile, cloud and multi-media computing can now support robust “citizen science” campaigns. Accordingly, we developed MESA 3.0 ― an android application that conducts site-specific mapping. This “app” is the next-gen version of early MESA systems (Harte et al., 1999; Houran et al., 1998) and was designed to document and quantify anomalous experiences in real-time for cross-correlation with time-synced environmental readings.

Method: MESA 3.0 uses the sensors in mobile devices to measure GMF 3-axis, Lighting Levels, Temperature, Barometric Pressure, and Gravity/Acceleration. Data are collected at five samples per second, creating mini-packets of 25 readings every five seconds. Environmental data, audio, and pictures are aggregated, logged, and displayed to users via descriptive statistics and automatically saved in shareable files, which allow for uploading with a corresponding cloud-based data repository. The app further documents the installed sensor type, sensitivity, and resolution. Inclusion of the new Survey of Strange Events (SSE: Houran et al., 2019) also facilitates standardized comparisons of percipients' reports across environmental settings. We field-tested MESA 3.0’s four functional modes (i.e., Baseline, Freestyle, Sentinel, and EVP-Knock) via an exercise with volunteers who collected (a) baseline readings of their residences, (b) a baseline of a public area, and (c) baseline readings at a reputed “haunt.”

Results: The app performed as designed — environmental data were easily retrieved, compared against photographs and SSE scores, as well as automatically stored and available to download for statistical analysis. We noted some variability across different mobile devices, but overall, the environmental readings and investigation protocol were stable across users and hardware. Thus, the app was an effective method to obtain “environmental and experiential maps” of settings associated with anomalous experiences.

Discussion: MESA 3.0 is a user-friendly mobile lab that can be used in research designs involving citizen scientists. I.S.R.A.E will host and maintain the application’s platform and open-access data repository. Our intention is to engage several thousand enthusiasts to create the largest documented set of public data for “haunted, sacred or enchanted” locations to date. As such, we hope this effort can help to mend antagonistic relationships between parapsychologists and ghost-hunters (Hill et al., 2018, 2019; Houran, 2017) by introducing this tool to amateur paranormal groups for structured and productive future collaborations between the two camps. Collaboration for further application and refinement of MESA 3.0 is open and welcome.

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A Citizen Science Tool for Big-Data on Ghostly Episodes

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