Word Cloud

From student voices to knowledge discovery.

This word cloud was created based on a corpus of deidentified transcripts from student media stories submitted to the Social Media & Ourselves podcast. Interns in the School of Information Master of Library and Information Science program have worked with Dr. Hong Cui to develop and refine a taxonomy based on this growing corpus since the spring of 2021.

Wordcloud.R was used to generate the word.frequency.cvs, word.ti.idf.cvs, and the word clouds pgn files: : generated using tf.idf scores, with the threshold = 0.4 (it. Words that scored 0.4 and aboved are included in the cloud)


More about iVoices Research

Open Pedagogy: Independence and Interdependence in Teaching About New Media

Learn about research we facilitate by Cheryl Casey, the University of Arizona's Open Education Librarian, on students' responses to iVoices Media Lab in our big Gen Ed class.


Video with transcription here


View this Google Slides Presentation presented at the Hawaii University International Conference, January 5th 2022.


iVoices is a three year project funded in part by the Center for University Education and Scholarship, through a generous fellowship to Dr. Diana Daly. In research in 2022 and 2023, Dr. Daly and iVoices aim to address the following research questions:

  • How do undergraduate students' experiences with technologies shape their engagement in learning throughout their college careers? 
  • In what ways do students’ narratives around technologies enrich new media scholarship?
  • How do we best integrate student knowledge around technologies into new media curricula?
  • What are the impacts of training students in media production and leadership on students and their communities?
  • What are best practices for a media lab around student perspectives on social and educational technologies?

Additionally, beginning in Spring 2021, we are broadening our focus to include information, misinformation, and disinformation.

  •  Using collaborative media analysis and story production to fight disinformation
    • What practices and strategies are most successful in leveraging social identity and feedback toward the reinforcement of science and debunking of disinformation? 

iVoices is collecting and will make available over time open data sets including:

  • Instructor-created resources
  • Program evaluation survey results
  • Deidentified audio and transcript files
  • Social Media and Ourselves podcast-published student stories
  • Student audio, video, and written stories and images created through our media lab workshops and licensed CC-BY
  • Our Humans R Social Media course textbook, an Open Educational Resource

Access our Spring 2021 CC BY Media Collection and Dataset

QR Code for our Spring 2021 CC BY Media Collection

This dataset includes:

  • Content by 71 students in one semester
  • 467 Content items including
    • Graphic Profile Pictures with bios
    • Audio Stories
    • Video Stories
    • Original Memes
  • Searchable transcriptions 
  • Key words and visualizations 
  • Human- and machine-readable versions for mixed method analysis


The Fall 20 and Fall 21 Collections and Datasets will be released this year.