Open chennesy opened 4 years ago
ChristinaLK
commented
4 years ago thanks for submitting @chennesy ! We're hoping to invite community feedback next week - if you would like additional contributions or help with this session, or just want to highlight how people can be involved, add a comment at the end of the issue with that information.
ousodaniel
commented
4 years ago @chennesy thanks for your interest in regional hosting, check out the details here please. We'd love to see you sign up. Best
serahkiburu
commented
4 years ago Hi @chennesy, the organising committee reviewed this session proposal and had this to say:
This is a breakout discussion on building community based on specific skill requirement, in this case it is text analysis skills (text as data).We are excited about this session to introduce community members to the topic of community building around text-as-data. Their topic fits very well, but the first part of the abstract can be shortened to ensure that they don't mislead the interested attendees into assuming that they will learn about text-as-data and analysis skills. If the session leads are interested, they are invited to run a second session as skill-up on text analysis skill as well assuming that there will be an interest for that.
We are so excited for your session, and more details i.e. around scheduling will be shared with you in the coming days. Thanks Cody 🙌
Title of the session: Building Text-as-Data Communities
Session details
Session type: Breakout discussion
Keywords: text analytics, communities of practice
Permission to record this session: Yes
Abstract
In this session we hope to bring together text-as-data practitioners and those in academic support roles to discuss models for building communities related to computational text analysis. Many early career scholars interested in text analytics find themselves at institutions that provide little direct support for learning and practicing emerging methods related to text as data (e.g., topic modeling or sentiment analysis). Even where expertise does exist on a particular campus, it can be difficult for an individual scholar—especially those in the humanities or social sciences—to bridge disciplinary and bureaucratic boundaries to find peers and mentors in computational research areas. The Carpentries offer one helpful foundation for learning essential data science tools; this session explores opportunities for building upon that foundation to address the growing needs and interests of scholars in text analytics.
At our institution, we recently initiated the Text as Data Practice Group, a discipline-agnostic monthly gathering for scholars to experiment and learn from each other, from local experts, and from open access tutorials in a social setting. The group operates in the spirit of creating community, nurturing peer-to-peer learning, and exploring emerging text and data analysis methods on campus. We plan to provide an overview of this program, and then lead participants through discussion prompts to share their own thoughts about successes, challenges, and opportunities related to building communities for text as data. Participants will learn about different models to develop and nurture communities in computational research.
Personal details
Name or pseudoname of the session lead: Cody Hennesy
Co-leads' names (we recommend involving 2 helpers/co-leads): Alexis Logsdon, Wanda Marsolek
Email or other ways to contact the session leads/co-leads: chennesy@umn.edu, mars0215@umn.edu, logs0002@umn.edu
Country of residence and/or compatible Time Zones (provide options): United States, UTC/GMT -5:00 hours (Central Daylight Time)
Would you like to present this multiple times, in other time zones: No
Would you like to volunteer to be listed as a wrangler/host for your time zone: Yes (Cody Hennesy: chennesy@umn.edu)
Is there any help you would like to invite from the community? Please provide below in bullet points.