Dataset Details

This dataset contains a rich collection of popular slang terms and acronyms used primarily by Generation Z. It includes detailed descriptions of each term, its context of use, and practical examples that demonstrate how the slang is used in real-life conversations. The dataset is designed to capture the unique and evolving language patterns of GenZ, reflecting their communication style in digital spaces such as social media, text messaging, and online forums. Each… See the full description on the dataset page: https://huggingface.co/datasets/MLBtrio/genz-slang-dataset.

This dataset provides insights into the spending habits of Gen Z (ages 18-27) across various categories such as rent, groceries, entertainment, education, savings, and more. It contains 1700 records and 15 financial attributes, making it a valuable resource for financial trend analysis, budgeting studies, and machine learning applications in personal finance.

The Zoroastrian community today faces many challenges, some of which are deep-rooted and complex with no easy fix or resolution. It was proposed by members of the community that an independent research project should be conducted to help understand the community as it exists today. Gen Z and Beyond: A Survey for Every Generation was a completely anonymous survey for Iranian / Parsi / Irani Zoroastrians. It was conducted by researchers at the SOAS Shapoorji Pallonji Institute of Zoroastrian Studies (SSPIZS). SOAS was chosen as a neutral platform for research, so that the researchers would not support any particular outcome from the survey. The project was approved by the SOAS Research Ethics Panel. There has been no other survey of this nature undertaken on the global Zoroastrian community. The survey questionnaire was wide-ranging and included questions about domestic and family life, professional aspirations, religious observances and beliefs, philanthropy, entrepreneurship, immigration, community engagement and other issues of importance and relevance to the (Iranian / Parsi / Irani) Zoroastrian community. The purpose of conducting the survey was to produce a report and dataset that could be of use to community leaders and researchers in the present and future.

This dataset contains audio recordings of 12 different accents across the UK: Northern Ireland, Scotland, Wales, North East England, North West England, Yorkshire and Humber, East Midlands, West Midlands, East of England, Greater London, South East England, South West England. We split the data into a Male: Female ratio of 1:1. The audio dataset was compiled using opensource YouTube videos and it a collation of different accents, the audio files were trimmed for uniformity. The Audio files are of length 30 seconds, with the first 5 seconds and last 5 seconds of the signal being blank. We also resample the audio signals at 8 kHz, again for uniformity and to remove any noise present in the audio signals whilst retaining the underlying characteristics. The intended application of this dataset was to be used in conjunction with a deep neural network for accent and gender classification tasks.

This dataset was recorded for an experimentation looking into applying machine learning techniques for the task of classifying song preference amongst generation Z (18 to 24 years) participants. We define a labelling system corresponding to specific songs with 5 ratings: hate, dislike, neutral, like and love. The songs used for this experiment were chosen due their success for various awards, such as the BRIT awards (BRIT), Mercury Prize (MERC), Rolling Stone most influential albums (ROLS). They are as shown:

S1: One Kiss by Calvin Harris and Dua Lipa (BRIT)

S2: Don't Delete the Kisses by Wolf Alice MERC)

S3: Money by Pink Floyd (ROLS)

S4: Shotgun by George Ezra (BRIT)

S5: Location by Dave (MERC)

S6: Smells Like Teen Spirit by Nirvana (ROLS)

S7: God's Plan by Drake (BRIT)

S8: Breezeblocks by alt-J (MERC)

S9: Lucy In The Sky With Diamonds by The Beatles (ROLS)

S10: Thank U, Next by Ariana Grande (BRIT)

S11: Shutdown by Skepta (MERC)

S12: Billie Jean by Micheal Jackson (ROLS)

A Unicorn Hybrid Black was used for recording the EEG data from the participants whilst they were played the control songs listed above. For each of the 12 total song played to a participant during the experiment, there were 8 EEG lead recordings measured of length 20 seconds, with the first 5 seconds and the last 5 seconds being blank for control purposes. The EEG signals were sampled at 250 Hz by the Unicorn Hybrid Black devices, which also filtered the signals to be between 2Hz to 30 Hz in order to remove any noise recorded during the experimentation. There are approximately 5000 data points per reading of a given song, with there being 12 songs played to a total of 10 participants.

ai-maker-space/gen-z-translation dataset hosted on Hugging Face and contributed by the HF Datasets community

Demographic and PII data (including emails, phone numbers, and addresses) for the US Millennial and Gen Z population segments. Fully opt-in and CCPA compliant (direct submission from the individuals). 30 million+ population.

High success and conversion rates for direct marketing, targeted ads, identity verification, and demographic research.

This data can be merged into the BIGDBM Consumer dataset or have specific data fields appended from the BIGDBM Consumer dataset.

BIGDBM Privacy Policy: https://bigdbm.com/privacy.html

This dataset contains the results of a survey conducted via Google Forms to assess Generation Z’s understanding, environmental awareness, and social action related to waste management during the Eid al-Fitr holiday season. The survey included an infographic guide as a stimulus to evaluate how visual media supports behavioral change and sustainability education among youth. The dataset also contains the result that had been transcribed from an interview with carbon expert.

The dataset, exported from Google Forms in XLSX format, includes respondents’ demographic information, their interpretation of the infographic content, their level of environmental awareness, and their reported or intended waste management practices during the holiday. The dataset from interviews with carbon expert, exported in DOCX format.

This dataset is valuable for researchers in environmental education, youth studies, sustainability communication, and behavioral change research.

Format: XLSX (exported from Google Forms)
Number of Respondents: 6
Language: Indonesia
License: Creative Commons Attribution 4.0 International (CC BY 4.0)
Data Collection Method: Online survey using Google Forms
Data Collection Period: 4 April 2025

How it Started

I was interested in collecting data about how Generation Z makes decisions because college is on the horizon for my classmates and me. We are becoming the leaders, entrepreneurs, and creators of tomorrow and behind every successful person, is their ability to make the right decision at the right time.

How I Collected my Data

I collected my data through google forms and before the answers started to trickle in, I created my own hypothesis. I thought that most students in Generation Z would not be afraid to make decisions and that since they are one of the smartest generations, they would be able to tackle the task of picking which college is best for them and why.

Inspiration

I am very much aware that a lot of research is being done to find out more about Generation Z, but I was so inspired by my research coach, Coach Jo, who is currently doing research with Dr. Peggy Dawson about Generation Z and Productivity. I learned that Generation Z is by far the smartest generation, but our attention spans are cut short because of how much we use technology and the internet. This research will help find out whether technology and making decision affects Generation Z and how we, as a society, can make better decisions for better futures.

Gen Z Slang Pairs Corpus (1 K)

The Gen Z Slang Pairs Corpus (1 K) contains 1,000 everyday English sentences alongside their Gen Z–style slang rewrites. This dataset is designed for style-transfer, informal-language generation, and paraphrasing research. Use it to train models that transform formal or neutral sentences into expressive, youth‑oriented slang.

  Dataset Details

This dataset was generated programmatically using OpenAI GPT-4.1 Nano.

Language: English… See the full description on the dataset page: https://huggingface.co/datasets/Programmer-RD-AI/genz-slang-pairs-1k.

The dataset consists of responses collected via an online questionnaire targeting Generation Z individuals in Portugal. It focuses on understanding the adoption of AI-driven chatbots in the tourism and hospitality industries. The data includes demographic information, behavioral variables, and responses to constructs from the AI Device Use Acceptance (AIDUA) model, such as emotional reaction, performance expectancy, anthropomorphism, and social influence.

This is a survey of over 3,000 young Londoners that was completed in June 2020 in partnership with the Museum of London. This focuses on the key issues and concerns affecting young people aged between 16-24 and reviews the challenges they face and what needs to happen to help young people thrive across the capital. This dataset is being reviewed. The data will be made available again soon.

In 2023, the disposable income of a household led by a Millennial in the United States was 97,866 U.S. dollars per year. Households led by someone born in Generation X, however, had a disposable income of around 113,886 U.S. dollars in 2023.

This dataset contains responses from a survey analyzing the impact of digital literacy on Generation Z’s intention to invest in financial products through investment applications. The data includes key variables such as digital literacy levels, investment awareness, behavioral intention, perceived ease of use, perceived risk, and demographic factors. The study aims to identify the extent to which digital literacy influences financial decision-making among young investors and how technology adoption plays a role in shaping their investment behavior.

The dataset is structured to support statistical analysis, hypothesis testing, and predictive modeling, making it valuable for academic research, business insights, and financial technology development.

This dataset contains responses from 467 Indonesian Gen Z respondents who participated in a survey examining continuance intention in gamified digital news platforms. The dataset was collected as part of a study investigating how perceived usefulness, satisfaction, confirmation, and intrinsic motivation (competence, autonomy, relatedness) impact user engagement and retention.

This dataset is linked to the research titled Cultural Tourism in Vietnam: Theories, Policies, and Gen Z's Perspective. It contains data from 251 respondents, representing the sample used for analysis in the study. The dataset serves as the foundation for deriving key findings and insights presented in the research.

The interview protocol aims to gauge their perceptions and responses toward brand activism, with a focus on their interactions with brands endorsing social issues. Within this dataset, interviewees unpack their perspective on Gen Z attributes and evaluate their resonance with prevalent depictions. Central to the interview is the participants' feedback on prominent brand campaigns such as Nike's "JUST DO IT," Gillette's "We Believe," and Libresse/Bodyform's "Viva la Vulva," to name a few. Their analyses unveil perceptions of brand genuineness, the synergy between a brand's image and its advocated social concerns, and the overarching ramifications of brand activism on consumer purchasing decisions. In addition, the dataset broaches essential themes like social credibility, the influence of brand spokespeople, geographical variances in brand activism, and the prospective outcomes for customer fidelity and product pricing. This collection offers an in-depth glimpse into the intricate dynamics between Gen Z and brands during this period of intensified social and political awareness. This dataset comprises qualitative data obtained from interviews with 37 individuals from the Gen Z demographic, predominantly aged between 20-25 years. Of these participants, 53.3% identified as male (n=20), 40% as female (n=15), and 6.7% opted not to specify their gender (n=2). The participants for these interviews were strategically sourced using the snowballing technique between 2021 and 2022. Among them, 33 are international young adults who, at some point within the last 1-2 years, were studying or employed in the Netherlands. It is noteworthy that between October 2021 and February 2022, the Netherlands observed a stringent lockdown, mandating remote work. Consequently, some interviewees, despite affiliations with Dutch organizations, were in their home countries during their respective interviews. The distribution of participants based on their continents of origin, namely North America, Europe, and Asia, and taking into account their place of residence in instances of dual citizenship, is detailed as follows: 1) Europe has the predominant representation with a sum of 20 participants; 2) North America consists of 7 participants, all originating from the USA; 3) Asia comprises 6 participants spread across four countries: Vietnam, Indonesia, Japan, and South Korea. Additionally, 4) South America is denoted by one participant from Bolivia and another participant holding dual citizenship from Argentina but currently residing in the US.

In the past, a generation covered a larger span of time, having more members. However, today, thanks to the developments in technology and many other factors generations change frequently having less members and covering a few years. What matters now is the workforce itself and how these different generations work together. The current workforce has 3 generations working together while waiting for the fourth one. Soon, it is inevitable that 5 or 6 generations will be working at the same workplace. As a result, it is crucial to understand the type of leadership a generation prefers in business and academic life. The aim of this study was to find out how leadership style choice differs among four generations (Baby Boomers, Generations X, Generation Y, and Generation Z) of academics and prospective academics in Turkey. In the study, 265 participants from different generation rated the leadership attributes that contribute or impede effective leadership. The Global Leadership and Organizational Behavior Effectiveness (GLOBE) Project research survey by House et al. (2004) was used to find out the leadership style choice of different generations. The statistical relationships were determined between the generation variable and the 16 primary leadership subscales through MANOVAs and ANOVAs. The results of the tests showed that significant differences exist among the four different generations in 3 of the 16 leadership subscales. These subscales are Charismatic 3: Self-sacrifice, Conflict-inducer, and Face saver.

Globalization has made human mobility high and the employment sector in a tight competition. In this era of globalization, all workers from various countries can find the same point of competition, Indonesia is no exception. Indonesia has a high population surplus and Indonesia also has a population dominated by productive generations. However, the era of globalization also brings a quite worrying impact, namely in the age of free competition. With the implementation of free trade cooperation, many foreign workers must be allowed to work in Indonesia and compete freely with workers from Indonesia. Competitiveness is crucial to keep Indonesian workers have a sense of competitiveness with workers from other countries (Ernst & Haar, 2019). The purpose of this study is to determine the competitiveness of Generation Z in the face of a free work competition in the disruptive era by identifying some main ideas about preparing and equipping Generation Z in developing portfolios and skills needed by the world of work. This research will use two option methods. The first method is a quantitative paradigm by using a questionnaire as a tool to determine the respondent's perspective with some questions. The second method is a qualitative paradigm by using a focus group discussion to describe a detail of the phenomenon to be analyzed comprehensively.

This dataset aims to determine the views, perceptions and behaviours of Generation Z in South Africa towards health crisis communication during the COVID-19 pandemic. The data was collected through semi-structured face-to-face interviews, and the 12 participants were selected from across the gender among Gen Z at the University of Pretoria. These interviews dwelled on areas like trust in government messaging, adherence to health measures, using social and digital platforms to share information and attitudes towards contradictory or inconsistent health information.The semi-structured interview methodology combining some extent of formal questions and answers with detailed participants’ descriptions gave profound qualitative data. It was, therefore, essential to come up with questions that would bring out episodes, feelings and thought processes that people went through during the pandemic. This way of working was helpful in thoroughly investigating the topics of interest while respecting the participants’ priorities. The dataset is central to this part of the analysis because cognitive dissonance, communication strategies, and behavioural outcomes are presumably linked in this population.

This dataset analyzed (1) the relationship between consumer attitudes, subjective norms, and perceived controls with the purchase intention of eco-friendly products in Generation Z consumers