Nicholas A. Christakis ✓
@NAChristakis · Vermont, USA · joined 29 Aug 2012
Sterling Professor of Social and Natural Science at Yale. Physician. Author of Apollo's Arrow; Blueprint; and Connected. ::: More active at azure skies.
185 824Followers
750Following
53 694Posts total
59.4KViews on collected posts
Neueste Beiträge
Wir suchen neue Beiträge…
Fine essay via @paulg "How Universities Should Prepare Founders": https://t.co/EMKqB3Nimt
Would that universities would listen, as there would be other benefits to pedagogy, too.
"The people you need to impress are users, not investors, and the way you impress them is with
6.2K views · 11 likes
· 1 reposts · 1 replies
Open on X →
@NAChristakis Super cool thread, Dr. Christakis. I was at the ASA conference earlier this month & one of your co-authors presented your joint work on social networks and homophily. So happy to see cognitive social psychology and network science complementing each other.
28 views · 1 likes
· 0 reposts · 0 replies
Open on X →
Experiments and field trials show how to exploit an understanding of social network structure and function to enhance human welfare. We can use an understanding of social networks, and of social contagion theory, to intervene in human populations, whether online or in person. 20/
1.5K views · 8 likes
· 0 reposts · 1 replies
Open on X →
Social contagion is relevant to phenomena as diverse as public goods production, inequality, technology adoption, economic productivity, political mobilization, misinformation, violence, emotional experience, health behavior, and epidemic disease. 19/
1.5K views · 6 likes
· 0 reposts · 1 replies
Open on X →
Humans are naturally embedded in complex, face-to-face social networks. These networks obey particular mathematical and social rules, and taking this into account offers profound new opportunities to understand and modify human behavior and collective outcomes , including public
183 views · 4 likes
· 0 reposts · 1 replies
Open on X →
“Simple Autonomous Agents Can Enhance Creative Semantic Discovery in Human Groups,” Nature Communications2024;14:5212. Groups are better able to identify and preserve innovations than individuals. We show that bots can enhance the creativity of human groups.
181 views · 5 likes
· 1 reposts · 1 replies
Open on X →
“Bringing Leaders of Network Subgroups Closer Together Does Not Facilitate Consensus,” Scientific Reports2024;14:30183. We find no evidence that the geodesic distance between leaders of two groups is a significant factor in the probability of reaching consensus.
182 views · 4 likes
· 1 reposts · 1 replies
Open on X →
“Status Invisibility Alleviates the Economic Gradient in Happiness in Social Network Experiments,” Nature Mental Health 2023;1:990. Making wealth invisible improves the subjective well-being of poor subjects and thus alleviates the economic gradient in SWB.
219 views · 5 likes
· 1 reposts · 1 replies
Open on X →
“Emergence and Collapse of Reciprocity in Semiautomatic Driving Coordination Experiments with Humans,” PNAS2023;120:e2307804120. Using remote-control cars in a game of “chicken,” we show that altruism collapses when people leave coordination decisions to machines. https://t.co/s1
2.2K views · 5 likes
· 4 reposts · 2 replies
Open on X →
“Network Engineering Using Autonomous Agents Increases Cooperation in Human Groups,” iScience 2020;23:101438. Simple AI bots can foster cooperation in human groups by using a re-wiring strategy designed to support the development of cooperative clusters. https://t.co/aPVE4ibG4H
2.5K views · 8 likes
· 2 reposts · 1 replies
Open on X →
“Assortative Mixing and Resource Inequality Enhance Collective Welfare in Sharing Networks,” PNAS 2019;116:22442. Resources and ties can be allocated in a network in a way that optimizes collective welfare, but at no increased overall cost. https://t.co/S6uxOJbWrt 11/
212 views · 4 likes
· 1 reposts · 1 replies
Open on X →
“Resource Sharing in Technologically Defined Social Networks,” Nature Communications 2019;10:1079. Sharing-economy networks are changing the way humans trade and collaborate. These networks can be structured to maximize collective welfare. https://t.co/I98F4ofnCW 10/
199 views · 3 likes
· 0 reposts · 1 replies
Open on X →
“Intermediate Levels of Network Fluidity Amplify Economic Growth and Mitigate Economic Inequality in Experimental Social Networks,” Sociological Science 2015;2:544. Increasing network fluidity fosters economic growth and lowers inequality, up to a point. https://t.co/t9oyyIdr6x
204 views · 4 likes
· 0 reposts · 1 replies
Open on X →
“Locally Noisy Autonomous Agents Improve Global Human Coordination in Network Experiments,” Nature2017;545:370. AI bots in groups facing a coordination challenge demonstrate the benefits of noise in collective decision making. Bots help humans to help themselves.
193 views · 3 likes
· 0 reposts · 1 replies
Open on X →
“Static Network Structure Can Stabilize Human Cooperation,” PNAS 2014;111:17093. Consistent with evolutionary game theory, when the benefit-to-cost ratio of cooperation exceeds the average network degree (b/c>k), even a static network structure can stabilize cooperation.
258 views · 3 likes
· 0 reposts · 1 replies
Open on X →
“Inequality and Visibility of Wealth in Experimental Social Networks,” Nature 2015;526:426. Making wealth visible in groups lowers overall cooperation, connection, and wealth. High initial levels of economic inequality alone, however, have few bad welfare effects.
221 views · 3 likes
· 0 reposts · 1 replies
Open on X →
“Quality Versus Quantity of Social Ties in Experimental Cooperative Networks,” Nature Communications 2013;4:2814. There is a Goldilocks effect of network dynamism on cooperation. Optimal levels of cooperation are achieved at intermediate levels of change in social ties.
2.3K views · 7 likes
· 2 reposts · 1 replies
Open on X →
“Dynamic Social Networks Promote Cooperation in Experiments with Humans,” PNAS 2011;108:19193. Experiments confirm evolutionary game theoretic models, demonstrating important role that dynamic social networks play in supporting large-scale cooperation. https://t.co/UQGONKmowi 4/
2K views · 12 likes
· 1 reposts · 1 replies
Open on X →
“Cooperative Behavior Cascades in Human Social Networks,” PNAS 2010;107:5334. These results show experimentally that cooperative behavior cascades in human social networks, to three degrees of separation, via social contagion. https://t.co/lhd8qM9mwn 3/ https://t.co/tQms1YeeP5
2.3K views · 7 likes
· 2 reposts · 1 replies
Open on X →
To sustain cooperation and related collective action in human groups, one way is “adding structure” by arranging people in networks or otherwise constraining their interactions (classic review: https://t.co/ZheP9X0f28).
We have used experiments to explore this. 2/
678 views · 4 likes
· 1 reposts · 1 replies
Open on X →
What role do social networks – and the precise nature and structure of social interactions – play in the production of public goods and in human welfare? What about social contagion? A thread on #HNL experiments with many thousands of participants from 2010 to the present. 1/ htt
10.8K views · 116 likes
· 35 reposts · 2 replies
Open on X →
New FLOS video: How to Assemble your Dissertation Committee: https://t.co/dWD1V2YEvI
7.5K views · 5 likes
· 1 reposts · 1 replies
Open on X →
@PNASNews On the path to machine olfaction. https://t.co/UZN8ilSQGH
1.7K views · 5 likes
· 3 reposts · 0 replies
Open on X →
@NAChristakis @PNASNews Does this connect with networks via Nietszhe's insistence that people connect by smell?
116 views · 1 likes
· 0 reposts · 1 replies
Open on X →
Olfaction lacks a quantitative framework similar to vision and hearing.
In new #HNL work in @PNASNews, we show that odor mixture perception can be predicted. This lays a foundation for digital olfaction, machine-readable smell metrics, next-generation electronic noses, and
8.1K views · 41 likes
· 5 reposts · 2 replies
Open on X →
Sometimes, when you are doing research, you become so obsessed with hidden reasons for things that you miss the manifest reasons.
https://t.co/wQuAxIc2SX
8K views · 7 likes
· 0 reposts · 0 replies
Open on X →
Im Vergleich zu Konten gleicher Größe
26 Beiträge aus den letzten 90 Tagen, verglichen mit der Größenklasse 100K–1M Follower. erreicht weniger Menschen als Konten gleicher Größe.
Medianaufrufe1 079dieses Konto5 886Median für 100K–1M
Reichweite, %0.58%dieses Konto1.87%Median für 100K–1M
Interaktion, %1.16%dieses Konto1.16%Median für 100K–1M
| Kennzahl | Dieses Konto | Median für 100K–1M | Verhältnis |
|---|---|---|---|
| Medianaufrufe pro Beitrag | 1 079 | 5 886 | 0.18× |
| Reichweite (Aufrufe ÷ Follower) | 0.58% | 1.87% | 0.31× |
| Interaktionsrate | 1.16% | 1.16% | 0.99× |
Weitere Konten dieser Größe → Mit einem anderen Konto vergleichen → Wie diese Vergleichswerte entstehen →
Growth & engagement
How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.
Views per post
19326 Aug
204
199
212
2.5K
2.2K
219
182
181
183
1.5K
1.5K
2827 Aug
6.2K28 Aug
Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.
Engagement rate per post
2.07%26 Aug
2.45%
2.01%
2.83%
0.44%
0.49%
3.20%
3.30%
3.87%
2.73%
0.47%
0.59%
3.57%27 Aug
0.21%28 Aug
Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 1.16%.
What the audience does
Likes55.8%282 in total
Reposts12.1%61 in total
Replies5.1%26 in total
Quotes0.2%1 in total
Bookmarks26.7%135 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.
Ähnliche Konten
Nux
@Nux_Taku
371.6K followers
· 6.6K posts
Nymphaaea 🔮 ✓
@NymphaaeaVT
371.6K followers
· 12.9K posts
Ministry of Coal ✓
@CoalMinistry
371.6K followers
· 16.9K posts
United Football League ✓
@TheUFL
371.6K followers
· 22.9K posts
نجيب محفوظ
@NajeeBMahfouZ_
371.6K followers
· 6.9K posts
حامد البلوي ✓
@hamed4848
371.6K followers
· 6.1K posts
Mxnkind ✓
@mxnkind_
371.6K followers
· 3K posts
John Hartson ✓
@JohnHartson10
371.5K followers
· 17.3K posts