#RESIST – How a hashtag united people over social media and beyond


When President Donald J. Trump was elected President of the United States, it was met with a bundle of mixed feelings. Some thought they finally had a representative in the white house that would look out for them, whilst others wept, rallied, and organized themselves. Out of the latter a new hashtag was born on social media: Resist.

#Resist has been used by several different individuals, groups, and organizations. Its spread and representation goes from social media into real life. Whilst empirical studies are surprisingly few, we do know that with Facebook’s over 1.5 billion users it has altered the social fabric as we know it, and on a societal level social media has created unprecedented opportunities for information flow, affective expression, social influence, and even democratic revolution (Lewis, Gray, and Meierhenrich 2014:1).

The meaning behind the hashtag ‘Resist’ may vary from person to person, and the way people use it come in variations. Founders and executive directors of groups around the United States explain what #Resist really mean to them, listing some of the same core values, yet with personal take as well. According to them ‘Resist’ means to stand up, to fight, to not give in, to not become complacent or accept, to be be informed, to welcome diversity and differences, to join the masses, to protect their country’s gains and advances, and to move forward not backward. The resistance has taken centre stage as well. Recently, celebrities have made political anti-Trump statements through speeches, songs, and performances during both the Grammys as well as the Oscars. Katy Perry was seen wearing an armband with the word Resist on it during her performance at the Grammys.

The website meetup.com have created a space as well as encouraged individuals to join or start meetup groups for those who care about what’s happening to democracy, human rights, social justice, equality, sustainability, and other issues in their area. These groups can primarily be found all around the United States, but also in Australia, Ireland, and the United Kingdom.

On January 25, 2017, seven activists for Greenpeace, the environmental advocacy organization, climbed a crane near the White House in Washington DC and unfolded a banner with the word “Resist” on it. In Donald J. Trump’s first week in office he had taken steps to freeze grants through the Environmental Protection Agency and has resurrected the Keystone and Dakota Pipeline projects, something former President Barack Obama had put a stop to after months of protests by environmental activists. Travis Nichols, a spokesman for Greenpeace, said the protesters were there “to resist the environmental, economic and racial injustice that Trump and his administration have already laid out and put into practice.”

In my searches online it has been difficult to find any tallies of how often #resist has been used and any researches as to see the impact it has had on the wider community. Guo and Saxton writes that out of 53 advocacy groups in the United States most used social media to facilitate civic engagement and collective action. The authors continue writing that scholars have yet to delve deeper into the ‘statuses’ and ‘updates’ on social media sites such as Facebook and Twitter which brings us to the fact that in reality we know little about advocacy organizations’ social media presence (Guo and Saxton 2014:60f).

On an everyday basis, Mr. Boyan shares a recent experience: “I was on the phone arranging a [carpool] to violin practice and I said: ‘All right, I’ll be there in 20 minutes. Bye.’ And the mom said, ‘Resist,’” he continues, “When people say goodbye to each other, they are saying, ‘Resist.’” It appears that the hashtag resist is much more than just a ‘thing’ on the internet, it has become a representation of something much bigger that resonates with many.

References – imbedded in the text and:

Guo, C., Saxton, G.D. 2014- Tweeting Social Change- How Social Media Are Changing Nonprofit Advocacy, Nonprofit and Voluntary Sector Quarterly.

Lewis, K., Gray, K., & Meierhenrich, J. 2014- The Structure of Online Activism, Sociological Science.

Do you “like” your future?

Tell me, what you eat and I will tell you who you are – this famous quote by the French chef and artist Jean Anthelme Brillat-Savarin came to my mind when I first heard about the company Cambridge Analytica. The company who claims they are able to evaluate one’s personality better than their friends – just based on the access to the person’s facebook page. This London-based company advised the Trump’s presidential campaign – and now states they were able to help him win the run, using their state of the art analysis. Welcome to the world of Big Data!

“Everything we do, both on and offline, leaves digital traces. Every purchase we make with our cards, every search we type into Google, every movement we make when our mobile phone is in our pocket, every “like” is stored,” describes Hannes Grassegger in an article for web Motherboard.[1]

The story of Cambridge Analytica goes back to 2012 when psychologist Michal Kosinski developed something called  MyPersonality app. This platform enabled users to create their personality profile by means of filling out different psychometric questionnaires. Then Kosinski’s team compared the data with the “likes” people shared on their Facebook profile.

After many refinements of the modeling they came up with extraordinary results: “They were able to evaluate a person better than the average work colleague, merely on the basis of ten Facebook “likes.” Seventy “likes” were enough to outdo what a person’s friends knew, 150 what their parents knew, and 300 “likes” what their partner knew. More “likes” could even surpass what a person thought they knew about themselves,[2]” describes Grassegger.
We usually do not think about what we “like” on Facebook. But showing the musicians we prefer, books we read or media we follow, we are providing companies such as Cambridge Analytica with very useful material for evaluation. Then it is just a matter for them of using/having powerful algorithms to focus their campaign on a specific audience. Theoretically, in the presidential campaign, this would mean that the advertising agency could only focus on a small group of undecided voters with a potential to support their candidate, not spending any money outside of potential electorate.
But as Leonid Bershidsky shows – it is not that easy: “Huge data sets are often less helpful in understanding an electorate than one or two key data points — for instance, what issue is most important to a particular undecided voter.”[3] His small research shows that the level of analysis and targeting is not at all at the level as would suggest that the Cambridge Analytica strong statement claims.
At the moment, it does not look like that there is any company that powerful to win the presidential run. But the amount of data we are providing freely to the world is alarming. And no one can guarantee that at the time of the next US presidential run, there will not be a company able to win the elections just by means of precise targeting. That is something I am worried about. Big data might be powerful. By the way, have you heard that one of the biggest US e-commerce companies plan for the future is to have a drone with your order on the way to your house even before you placed the order? Guess how they know what you want…
[1] https://motherboard.vice.com/en_us/article/how-our-likes-helped-trump-win

[2]  https://motherboard.vice.com/en_us/article/how-our-likes-helped-trump-win

[3]  https://www.bloomberg.com/view/articles/2016-12-08/no-big-data-didn-t-win-the-u-s-election



Spotify gets banned in Sweden

Unusual events are more interesting, hence they manage to be in the headlines… The fact that the usage of a music streaming service would be banned in its actual birthplace is in itself paradoxical, yet probably more attention would be paid in today’s world of “info dump”.

Of course the title is fake news, no such plans am I aware of to the service now reportedly used by 100 million subscribers[1] including me.

This story began while I was on my way home from work listening to music randomly suggested by Spotify when a mellow, female voice accompanied by an acoustic guitar transported me somewhere peaceful in the middle of a cold winter night in Sweden. I could not understand the lyrics, as she sang in a language foreign to me, but somehow the voice was so captivating, I wanted to know more.

Google… Type… Search…

0,80 seconds later I learnt that she was born in Ivory Coast to Malian parents. As she refused to attend school her parents sent her at the age of 12 to live and be disciplined by an aunt in Bamako, Mali[2]. The aunt was an actress and she’s suddenly became surrounded by a creative world landing her a lead role at the age of 18 in Dani Kouyaté’s popular 2001 film Sia, The Dream of the Python. The movie tells the story of a West African legend called Sia, a young girl who defies tradition. Pressured by family to settle and get married, she fled to Paris to pursue a career in acting. During breaks while rehearsing she sang for her own amusement backstage and later on picked up the guitar: “To me it was a wonderful and daring thing: a Malian girl with an acoustic guitar. Why should the guitar be only for men?”. Her debut full length album was released in 2011, where she sings in her native language of Bambare. Her name is Fatoumata Diawara.

Her voice is delicate, yet the lyrics[3] are powerful covering a range of topics from war, abandonment of children, lives lost on sea while fleeing to Europe in Clandestin to female genital mutilation in song titled Boloko.

What do you know about Mali? Well, the landlocked West-African country experienced rapid economic growth after the 1990s, coupled with a flourishing democracy and relative social stability. In 2013, France intervened militarily upon the government’s request following the capture of the town of Konna and its troops overran Islamist strongholds.

The north remains tense, however, with both Tuareg separatists and Islamists sporadically active. Mali is renowned worldwide for having produced some of the stars of African music, most notably Salif Keita[4].

The country made headlines recently when Islamist radicals took hostage 170 people in the capital, Bamako at the Radisson Blu hotel. The terror attack has left 22 people dead.

Over the past two years, extremist groups have used Mali as a staging ground for attacks on hotels, beach resorts and restaurants in West Africa. “Women were whipped for wearing clothes deemed indecent, and thieves had their hands cut off. But the militants also banned music in a culture where griots, praise-singers and story-tellers are of great importance, and where music is considered the lifeblood of society[5]”. A well-known music festival, Festival au Désert was coming back to Timbuktu this year after years in exile, but officials blocked it last minute over security fears of an al-Queda attack.

The film Timbuktu captures the everyday life of this region with amongst others, music being banned and people punished for listening to it, while in another moment a couple gets stoned to death for adultery[6]. Fatoumata plays the singer who secretly plays a guitar and sings with friends at home, while we follow how they get captured, sentenced and later on punished. She also contributed with the soundtrack of the movie titled “Timbuktu Fasso”.

While it’s hard to imagine music being taken away and regarded as a sin, it is happening in some parts of the world. How do you translate Roskilde Festival taken away from the Danish audience? And what happens if you succeed? Does it transform from thought to something else?

Who cares?




[3]Translated to English

[4] http://www.bbc.com/news/world-africa-13881370


[6] Based on actual events in 2012 http://www.bbc.com/news/world-africa-19053442

Big Data Catches: Furthering Development, not the Divide

Women in the port of Bitung, Indonesia prepare the day’s catch for market. 

The global fishing industry is a multi-billion dollar industry, with a recent report released by Stratistics MRC valuing it at $239.8 billion in 2015 — and projecting it to reach $320 billion by 2022. Southeast Asia is one of the largest contributors to this market, accounting for more than 50% of the world catch and with the largest concentration of fishing vessels in the world– over 3 million. More than just an economic powerhouse and one of the globe’s biggest sources of protein, Southeast Asia’s fisheries employ 93% of all fishery and aquaculture employees worldwide, and 10% of the world’s total working population.

The industry, while growing and a profitable employer of hundreds of millions, is also a large developmental concern. Its exponential growth and increased demands that it enjoys negatively impact the health of valuable ecosystems, marine biodiversity, and threaten already dwindling fish stocks. In addition to the environmental impacts, the region is rife with illegal, unreported, and unregulated (IUU) fishing – an issue that is gaining traction in development both because of its environmental impacts, but also because of its serious human welfare implications.

“Data has become increasingly important to the way we think and talk about conflict and our humanitarian responses to it” (Róisín Read, Bertrand Taithe and Roger Mac Ginty). In a world where technology is often looked to to address human problems, how do these issues relate to data and development? A number of non-governmental, governmental, private sector, and industry players are increasingly looking to data to gather information on an industry that, despite its wealth, is incredibly challenged by tracking and sourcing its products, far behind other food sector’s traceability capabilities.

With new U.S. regulations that will require a set of standard data to be submitted with every seafood import to enhance transparency (released in December 2016 and going into effect in January 2018) also serving as a catalyst, fisherfolk and industry must quickly get aboard supply chain data collection efforts, and figure out how to implement these systems in their operations. Data collection is challenged by limited connectivity at sea, hesitancy to invest, unwillingness to share proprietary data (such as location of catch), and complex supply chains.

So, how can development organizations address this challenge to increase sustainability, protect finite marine resources, and address serious human welfare concerns that include limited labor rights, forced labor, and slavery? While more data can equal more intelligent decision making, transparency, and the development of effective policy and regulation, it can also leave beneficiaries behind – often the most critical beneficiaries, those that have sole-source incomes, limited access to technology, and depend on the sector for their livelihood.

Not only do large scale commercial operations need to be addressed, but small-scale fishers – those that often catch only a few kilograms of fish per day and is their sole source of income. How can large scale operators and artisanal fishers, living in small coastal fishing villages comply with regulations and uniformly collect data in a way that doesn’t push small, independent fishers out of the supply chain? With the proliferation of big data, how can development take care to further development goals with technology, and not further segment society into groups that are more or less likely to adopt data technology? “…The way information technology [has] operated in the sector [is] equivalent to ‘buying a state of the art car, driving it into the desert and leaving it there’. More and more money is invested in developing these technologies but their use is often limited, driven not by a clear sense of what is needed to improve response, but by what the advances in technology enable.”



Stratistics MRC. Commercial Fishing Industry – Global Market Outlook (2016-2022). January 2017. http://www.satprnews.com/2017/03/03/commercial-fishing-industry-market-size-share-analysis-report-and-forecast-to-2022/

Global Implications of Illegal, Unreported, and Unregulated (IUU) Fishing. National Intelligence Council. 19 September 2016. http://www.iuufishing.noaa.gov/RecommendationsandActions/RECOMMENDATION1415/FinalRuleTraceability.aspx
Third World Quarterly, 2016  Data hubris? Humanitarian information systems and the mirage of technology Róisín Read, Bertrand Taithe and Roger Mac Ginty Humanitarian and Conflict Response Institute, University of Manchester, UK. http://dx.doi.org/10.1080/01436597.2015.1136208

Big Data in Crises: Predicting the Future

Little ‘Data’, aNto on Flickr CC by A

Gathering, processing and interpreting data sets is what runs the modern global economy. Everything from your weekly online supermarket grocery shop, to how the shelves get stacked with goods delivered by cargo ships from all across the world. Teams of statisticians make their daily bread from finding more and more sophisticated ways of predicting human behaviour.

Complex mathematical modelling is also being used in humanitarian emergency situations to prevent further loss of life. I’m not just referring to how aid is delivered through more efficient supply chains, but to how the mapping of crises and outbreaks of diseases is used to instigate the correct response and predict how the spread is evolving.

Dr Sebastian Funk at the London School of Hygiene and Tropical medicine is a leader in the field and was at the centre of important work to map the Ebola outbreak in West Africa. By processing data collected from the affected area Dr Funk and peers across the world were able to look almost 6 weeks into the future, with 95% confidence of the first week.

Finding a ‘magic bullet’ or key to suppressing an outbreak is time sensitive – one must collect enough quality data to make sure that the models can be accurate, but when people’s lives are at stake conclusions need be drawn quickly.

It was found that ‘most people infected with the deadly virus became ill through contact with a small number of so-called ‘superspreaders’ and ‘if superspreading had been under control, about two-thirds of Ebola cases could have been avoided’.

Here he is speaking to RFI’s English service

Dr Funk’s work was reliant on effective feedback on the ground. He knew that whilst cases might be dropping off, there are unreported areas and if the superspreaders had been identified earlier, lives could have been saved.

The unprecedented rise of smartphone and social media has changed the data landscape. Agencies can have access to crowd-sourced information, which taken together can be highly accurate.

This was already happening during the Ebola outbreak – ‘When epidemiological data are scarce, social media and Internet reports can be reliable tools for forecasting infectious disease outbreaks’, from findings published in the Journal of Infectious Diseases.

Patrick Meier advocates the use of geographically mapping social media posts –  in Digital Humanitarians: how BIG DATA is changing the face of humanitarian response he describes crisis mapping of the 2010 Haitian earthquake and Libyan political turmoil in 2011 known as the Arab Spring. This approach allows aid workers to have a more complete live overview of the situation that’s constantly updated.

Libya Crisis Map Deployment 2011 Report

The crowd-sourced reports are collated by a volunteer team that work 24hrs a day, corroborating information from social media sources. It led to a significant change in the response, something which was praised by UNOCHA, if not without some reservations.

In this case, the role of the human as an arbiter of trustworthiness remains a significant undertaking. Even with pleas like: ‘we just need to make sure you’re not Gaddafi!…we are not Facebook!’ (Meier, p.125) for people to declare their background information, the digital gathering of sources, even on a big scale, still has to have an element of journalistic rigour.

The future will be to use artificial intelligence to perform checks that people simply don’t have the capacity to do, given the volume of information coming in. Systems are being developed that analyse qualitative rather than quantitative qualities of posts, allowing computers to detect false rumours and unrelated background noise.

With accurate models, the prediction capabilities in future outbreaks of disease or disaster will certainly be enhanced, leading to an untold impact on lives saved.

Leave your comments or tweet @data_bigly if you want to join the conversation.

References. Links in text plus:

Mier, Patrick. Digital Humanitarians: How BIG DATA Is Changing the Face of Humanitarian Response CRC Press, London. 2015

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