The Hive is a special projects unit of USA for UNHCR, the UN Refugee Agency. They are a team of digital and data strategists who find creative ways of addressing the global refugee crisis. One key area of focus for the Hive is to identify strategies to increase donations. This includes increasing donor engagement and shifting the conversation around refugees in the US.
The Hive wishes to identify social media users on Twitter who are influential, or have potential to be influential, in the online conversation about refugees. Knowing who these users are can help them better target their online outreach, and identify Twitter users who might become advocates for the Hive's messages about refugees.
Our team and the Hive agreed to create a tools which can help to identify Twitter users who have a history of tweeting about refugees, and have high reach and engagement. The tool identifies Twitter users in specific regions of the US whose tweets in relation to refugees are widely retweeted or replied to.
Please see the videos below, which show how the tool works.
Demo 1: The map interface, displaying the Twitter users by location, with the number of followers in circles. The panel on the right ranks the influencers visible in the map by their level of influence and attaches a label based on the following:
- 1K – 100K followers = MICRO influencers
- 100K – 500K followers = MID-tier influencers
- 500K – 2M followers = MACRO influencers
- 2M+ followers = all-STAR influencers
Demo 2: Once an influencer of interest has been identified, the user can click on their name, and will be taken to the Twitter page of that influencer.
npm install --save prop-types npm install --save google-map-react npm install --save react-controllables npm install @babel/plugin-proposal-decorators npm install --save react-splitter-layout npm install --save styled-components npm install --save react-instantsearch-dom npm install --save react-twitter-embed
| Member | Bio | |
|---|---|---|
| JK Hunt | jkhunt@stanford.edu | JK is an undergraduate student from London at Stanford studying Computer Science. He is interested in the intersection between social good and computer science, in particular machine learning and natural language processing. |
| Pamela Tham | pamtham@stanford.edu | Pamela is a student at the Graduate School of Education at Stanford. She is interested in creating and developing mastery in tools that support organizational improvement and better student outcomes. She has worked as an elementary school teacher and a civil servant in Singapore's Ministry of Education and Ministry of Finance, and is excited about how technology can help to improve access and equity in education. |
| Jessica Chen | jchens@stanford.edu | Jessica is ... |
| Sasankh Munukutla | sasankh@stanford.edu | Sasankh is an undergraduate student at Stanford studying Computer Science from Singapore. He is passionate about fusing technology and social impact. His past experience includes social service, software and hardware projects and military leadership. With an interest in NLP and broadening perspectives, he is excited about how this project can change the conversation around the refugee crisis. |
| Mustafa Khan | mkhan7@stanford.edu | Mustafa is an undergraduate Symbolic Systems major at Stanford from Lahore, Pakistan, concentrating in Artificial Intelligence. He has a background in social entrepreneurship and looks to delve into the intersection of technology and social impact. He is excited to launch this project to the benefit of changing the conversation about refugees. |
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Thank you to:
- The Hive: Nicole Smith
- CS + SG: Tess Rinaldo and Michelle Julia
Who are major Twitter Influencers regarding Refugees?
Influencer score (Raw) =
[Followers] * [Tweets] * [Retweets] * [Favorites]
Power BI formula = original_tweets[Followers]original_tweets[Tweets][retweet_count]*[favorite_count]/10^10
Influencer score (Weighted) =
( ( ([Retweets] *0.7) ^2 +([Favorites]*0.3)^2 ) / [Tweets] ) * Log([Followers])^3
Power BI formula = CALCULATE(divide((sum(original_tweets[retweet_count]).7)^2+(sum(original_tweets[favorite_count]).3)^2,sum(original_tweets[Tweets]))*[Log of Followers]^3/10^9,ALLEXCEPT(original_tweets,original_tweets[user.screen_name]))
@Refugees @UNRefugeeAgency asylum asylumseeker immigrants migrants refugee RefugeesWelcome rohingya rohingyarefugees syrianrefugee syrianrefugees TEDxKakumaCamp unhcr USA withrefugees
This list has a general positive word association with refugees and may (likely) excludes negative contributors that we want to focus on.
Recommend repeat exercise using “wider net” of terms Following list sample, not inclusive Assimilation Assisted Voluntary Return Border management Brain drain Brain gain Capacity building Circular migration Country of origin Emigration Facilitated migration Forced migration Freedom of movement Immigration Internally displaced person International minimum standards Irregular migration Labour migration Migration Migration management Naturalization Orderly migration Push-pull factors Receiving country Repatriation Remittances Resettlement Smuggling Stateless person Technical cooperation Trafficking in persons Xenophobia Alien Illegal Immigrant Illegals Undocumented Caravan UNHCR UN Refugees ICE deportation border wall illegal border crossing