This readme.txt file was generated on 2023-05-01 by Rose Guingrich

GENERAL INFORMATION

1. Title of Dataset: "Chatbots as social companions: Perceiving consciousness, human likeness, and social health benefits in machines"

2. Author Information
	A. Principal Investigator Contact Information
		Name: Michael Graziano
		Institution: Princeton University
		Address: Princeton Neuroscience Institute
		Email: graziano@princeton.edu

	B. Associate or Co-investigator Contact Information
		Name: Rose Guingrich
		Institution: Princeton University
		Address: Princeton Psychology Department
		Email: rose.guingrich@princeton.edu
 

3. Date of data collection (single date, range, approximate date): 01-02, 2023

4. Geographic location of data collection: N/A (online)

5. Information about funding sources that supported the collection of the data: Research supported by Grant 24400-B1459-FA010 from AE Studios, the National Science Foundation Graduate Research Fellowship, the Princeton Psychology Department, & the Joint Degree Program in Social Policy at Princeton.


SHARING/ACCESS INFORMATION

1. Licenses/restrictions placed on the data: CC-BY 4.0; code: MIT License

2. Links to publications that cite or use the data: TBD

3. Links to other publicly accessible locations of the data: N/A

4. Links/relationships to ancillary data sets: N/A

5. Was data derived from another source? No
	A. If yes, list source(s): 

6. Recommended citation for this dataset: Guingrich, R., & Graziano, M. (2023). Chatbots as social companions: Perceiving consciousness, human likeness, and social health benefits in machines [Data set]. Princeton University. https://doi.org/10.34770/8KYD-5V18


DATA & FILE OVERVIEW

1. File List: 

Chatbot_code: R Markdown file containing code to run experimental results (note: some column numbers may need to be altered before running; check that column numbers and names in comments align)

Dat_users.csv: Spreadsheet containing companion chatbot user results, in csv format for open access

Dat_control.csv: Spreadsheet containing non-user results, in csv format for open access

Free_response_users.xlsx: Spreadsheet containing companion chatbot user free responses, in Excel format for readability

Free_response_control.xlsx: Spreadsheet containing non-user free responses, in Excel format for readability

2. Relationship between files, if important: N/A

3. Additional related data collected that was not included in the current data package: N/A

4. Are there multiple versions of the dataset? No

5. Information about numerical fields in data:

Demographics:
# Country: (1) USA, (2) OTHER
# Ethnicity: (1) Hispanic, (2) Not Hispanic
# Race: (1) White or Caucasian, (2) Black or African American, (3) American Indian/Native American or Alaska Native, (4) Asian, (5) Native Hawaiian or Other Pacific Islander, (6) Other, (7) Prefer not to say
# Education: (1) Some high school or less, (2) High school diploma or GED, (3) Some college, but no degree, (4) Associates or technical degree, (5) Bachelor's degree, (6) Graduate or professional degree, (7) Prefer not to say
# Income: (1) Less than 25k, (2) 25-49k, (3) 50-74k, (4) 75-99k, (5) 100-149k, (6) 150k+, (7) Prefer not to say
# Age: (1) 18-24, (2) 25-34, (3) 35-44, (4) 45-54, (5) 55-64, (6) 65+
# Gender: (1) Male, (2) Female, (3) Non-binary/third gender, (4) Prefer to self-describe, (5) Prefer not to say
# Relationship status: (1) Married, (2) Living with a partner, (3) Widowed, (4) Divorced/separated, (5) Never been married

All others:
All non-demographic questions were asked on a 1-7 Likert scale.
Key: string begins with “x”, “score” = “indicates”
# social_health 7 = very helpful, 1 = very harmful
# experience/consciousness/personality/agency 7 = strongly agree / it has those things, 1 = strongly disagree
# natural/conscious/humanlike, etc. 7 = as much that as possible (7 = natural, 1 = fake, e.g.)
# if_emotions 7 = very comfortable 
# if_livingbeing / if_dependent 7 = very good

METHODOLOGICAL INFORMATION

1. Description of methods used for collection/generation of data: 
The study was conducted online through a major social media platform (Reddit). Participants followed a link to a Qualtrics survey.

2. Methods for processing the data: 
Data were processed in R Studio.

3. Instrument- or software-specific information needed to interpret the data: 
R Studio

4. Standards and calibration information, if appropriate: N/A

5. Environmental/experimental conditions: N/A

6. Describe any quality-assurance procedures performed on the data: N/A

7. People involved with sample collection, processing, analysis and/or submission: 
All model code was written or adapted by Rose Guingrich. Rose Guingrich conducted the collection and analysis of data.