Introducing “What We’re Reading”
This is the first post in a new series we’re launching called “What We’re Reading.”
In each post, we’ll curate and summarize a mix of news articles and insights that we find interesting and believe will be useful to RelSci customers.
The What We’re Reading series will combine content from a variety of sources, and each post will cover a range of topics including data journalism, the role of people and relationship data in business, and research on networking.
1. Nonprofit fundraising using AI
Nonprofit thought leader Beth Kanter, author of The Networked Nonprofit, writes on her blog that she is “actively researching the use of AI to scale generosity.”
Kanter attended Network For Good’s recent virtual conference Fundraise Like Netflix, and she writes that digital fundraising expert Adam Ruff’s presentation was especially memorable.
Ruff traced the history of nonprofit fundraising practices and outlined the challenge of scaling meaningful face-to-face engagement in a digital, always-on environment. He suggests that AI could offer a possible solution, if fundraisers adopt the following practices:
- Choosing the right AI tools
- Continuing to iterate, test, and learn
- Focusing on donor empathy
- Understanding donor behavior
- Using automation and AI to free up people’s time
2. Venture capital firm run by billionaire investor uses its financial services connections to find deals
PE Hub reports (paywall) that the venture capital firm Point72 Ventures, led by billionaire investor Steve Cohen, is leveraging its financial services industry network to source new investments in financial technology (fintech) companies.
Point72 Ventures is an independent arm of Cohen’s hedge fund Point72 Asset Management.
3. Reflections on the Knowledge Graph Conference
RelSci’s Chief Product Officer Emma Griffin attended the recent Knowledge Graph Conference hosted by Columbia University in New York. The conference brought together academics, data scientists, and business leaders to discuss the latest developments in knowledge graph technologies and applications.
Here are some of Emma’s reflections on the conference:
“It was fascinating to see the common threads that came up in each presentation – and in the side conversations during the breaks. It’s clear that the early adopters of knowledge graphs are all facing similar challenges, whether they be technical (data quality and standardization was a big one) or social, like how to alter a company culture to be receptive to a knowledge graph project.”
Other attendees reflected on the event in their own writing:
- Juan Sequeda, co-founder at Capsenta, was a presenter and member of the program committee. His Trip Report captures his main takeaways and summarizes many of the presentations.
- Vivek Khetan, who presented on his work at Accenture Labs, highlights his favorite presentations in his summary.
- A post on ZDNet dives deep into Uber Research Scientist Joshua Shinavier’s conference talk.
4. What’s the best way to network in a new job?
Organizational behavior experts Rob Cross and Peter Gray write in the Harvard Business Review that cultivating allies is key for anyone who hopes to hit the ground running when they start a new job. These allies help to create “a network of people who can provide the information, resources and support needed to succeed.”
Cross and Gray’s research has found that replicating the network of an established employee in a strong organizational culture typically takes three to five years.
But they wondered whether there was a way to accelerate that process, so they conducted an additional study to investigate. Here are a couple of their surprising findings:
- “Brand-building” across a broad network was not necessarily a better strategy. Instead, success newcomers were “more selective and less superficial in their outreach.”
- It wasn’t important for newcomers to have a strong relationship with a formal mentor or leader during their first nine months in their new role.
5. Who’s the most popular person in your city?
The journalist-engineers at The Pudding created a cool “People Map of the US,” which replaces cities and towns with the names of the most popular people associated with each place.
The popularity ranking is based on the amount of traffic to a given person’s Wikipedia page. The Pudding also created a version for the UK.
Reading something we should check out? Tweet @RelSci to let us know!