An Introduction to Science Communication

So, nice to meet you all. My name is Daisy Baisy. Um, I like to start with acknowledging that that rhymes. I think people get a bit confused about that. It's funny. [snorts] Um, I don't think I've met most of you. Um, so I'll introduce myself. I am El Life's social media manager. As Shane said, I joined El Life about 5 years ago. So, I've been here a long time. And I joined straight after doing a master's in science communication at Imperial College London. Uh before that I worked and volunteered mainly in educational settings, tutoring, uh museums and the like. And in today's talk, I'm going to try and give you a bit of a general introduction to science communication and and and an overview. Um, so we're going to start at the very beginning and we're going to talk about the philosophy of science and some general approaches to communication and then I'm going to drill down a little bit into some more practical considerations. And all of this is not purely from my expertise. I've done a lot of research for this and a lot of this is from contributions to my great colleagues at Elife across the organization. So I've got press and outreach thanks to Shane as well. And I will also share a copy of this presentation um through Shane afterwards because it includes some links and resources that you guys can use to read further because again I'm giving you an overview. There's a lot to talk about with science communication. So we'll start at the very beginning. We're going to talk about where we got our ideas about what science is as a foundation for how we communicate it. As scientists, you're trying to arrive at the truth of nature. And as science communicators, you're trying to share that truth with whoever, the public. Um, we need to be clear with ourselves what truth is. Is science the only valid form of knowledge? And what are our goals in communicating it? Are you trying to influence? Are you trying to inspire? Are your goals around self- advancement? Um, I'll preface this by saying we're looking probably mostly at Western philosophers here. These are the people that asserted themselves as the authorities on what science now is considered globally. So we can start with how philosophers and scientists long thought that scientists uh science should work. That's sometimes called the received view. We'll talk about this and I'll refer to this a few times. This is the idea that you observe the world, you collect facts and then you generalize from those observations. This is called a process of induction. An example of this approach is the white swan theory. If all of the swans you have ever seen in your life are white, you might make the conclusion that all swans are white as a fact. According to this view, there is one correct scientific method. You observe, hypothesize, and importantly seek to verify. Science was a process of verifying hypotheses drawn from observations. This differs, as you might have noticed, from how we think today. Um here science is assumed to be completely objective and completely value free. Scientists are rational and disinterested experts. The philosophers that upheld this approach tended to believe that science was the only valid source of knowledge and dis whoops and disregarded fields like the arts, ethics, religion, and so on. There are some obvious problems with the induction principle. It's possible that there will always be a counter example that disproves your theory. For example, you may one day see a black swan and that proves that swans are not always white. Just because you have only ever seen white swans, it doesn't mean the poss it doesn't rule out the possibility that a black swan exists. You just haven't seen it yet. A philosopher called Carl Pauper introduced the idea of falsification around the mid 1900s. He suggested that theory should come first rather than observation and you should test them against your observations. You make a hypothesis and then you seek to falsify it not verify it. Here to be scientific a theory has to make predictions that could in principle be proven wrong. The idea is to falsify not verify. When a prediction fails it can falsify the theory i.e. prove it wrong. But when it succeeds it doesn't prove it right. It just supports it for now. Science isn't about absolute certainty. It's more like a process of trial and error guided by criticism, debate, and repeated testing. It's incremental. We are approaching more and more truth. This, I'm sure, is now a more familiar idea of what science is to you guys. A guy called Thomas took this further. He noticed that science isn't just an incremental process like we thought before and that it's also social. and historical scientists operate with what he called paradigms that can be specific to their fields as well. Different disciplines might have different paradigms. These are shared frameworks or a culture that shape how they do science in that field. A paradigm includes the theories that are already accepted in the field, the standard problems that you might be solving, the methods and the instruments that you use, and even what criteria you have decided counts as a good explanation or counts as proof. Sometimes though, anomalies pile up and the old paradigm no longer explains them and then you get a scientific revolution. A paradigm shift is what would call it. like for example Newtonian mechanics giving way to Einsteinian relativity. showed that scientific change is often revolutionary not necessarily incremental and that it's partly shaped by the research community their shared culture and how they see the world. It's not just an incremental improvement but we make huge mistakes along the way because of the structures of knowledge we've built together as we go along. This now brings us to the idea of theory laden science and now closer again to probably the modern conception of a scientist. The old ideal portrayed scientists as perfectly neutral, disinterested seekers of the truth, totally objective and valuefree. But in reality, scientists are humans. They have careers. They have funding pressures and personal biases and values. On top of that we obser what we observe is never purely neutral. Observations are theory laden. They are shaped by the concepts the methods and the tools we use the the paradigms we have. It's us as humans that have designed the instruments define the parameters for significant results and us who interpret what we see. Subjectivity is baked into the systems that we have created and the data we produce. That doesn't invalidate science and it doesn't invalidate your work. What it means is that objectivity is a more collective achievement. We maintain it through peer review, through replication, and through critical scrutiny. Science works not because individual scientists are perfectly neutral, but because the community as a whole ideally holds each other accountable. Today, we tend to view science not as a single fixed method, but as a collective evolving enterprise. Knowledge doesn't just emerge from isolated geniuses following rigid steps. It's created by communities of researchers who question one another's assumptions, build on each other's works, and gradually or revolutionarily refine and replace ideas over time. Scientific process progress is iterative. Most of the time it advances through small improvements, but every so often an entire framework is overturned, replaced with a new way of seeing the world. And these shifts don't just happen because one person has perfect objectivity, but because the community tests claims from many angles. This is how increasingly we recognize the diversity strengthens objectivity. Different backgrounds, experiences, and values can help us identify blind spots that a single perspective would miss. And in this view, objectivity isn't what an individual scientist possesses. It's what the community achieves through open criticism, transparency, and inclusion. So the contemporary picture of science is one of a dynamic, socially embedded, self-correcting process rather than the purely neutral, perfectly disinterested activity it was once imagined to be. When we talk about the received view to understand how we communicate science, we also need to understand how people view it and how people trust or question scientific authority. Today, a lot of that trust can be built through a better public understanding of what science is, how it works, how it fails, and the philosophy of science we've just been talking about. Before we jump into the practical communication tools, it's it's worth grounding ourselves in the bigger picture. How does the public actually trust science today? Uh trust really matters. Most of us can't personally verify climate models or vaccine trials. So we're going to lean on institutions and experts to guide our thinking and make decisions for us. But when that trust is undermined, consider COVID and vaccine disinformation. Um everything downstream becomes harder. The policym public health guidance and even just our everyday decisions. People often say we're living in a post-truth era. I'm sure you've heard this and in many ways that is accurate. institutions like universities, scientific bodies, governments are under more scrutiny than ever. It's not always a bad thing. Scrutiny is healthy. But it does mean that this old idea of a scientist sort of being an automatically trusted authority just because they wear a lab coat doesn't hold anymore. What is interesting and there is a study that I think I've forgotten to link but I'll find it um is that trust in scientists themselves is globally still quite high. Um surveys show that scientists are still seen as competent, well-intentioned and importantly these surveys show that people think that scientists should be telling the public about their research. But the shakiness is more around the information environments, the media outlets, social media platforms, political institutions, um the the outlets that shape how scientific communication uh scientific information is communicated and interpreted. So in a in this very mixed moment, people broadly trust scientists, but they don't always trust the systems through which scientific knowledge reaches them. And that gap is exactly where good communication becomes most important. So if trust in science is partly shaped by how people perceive you, what can we actually do as communicators to strengthen it? A lot of the legacy thinking in science, i.e. the received view that we've just been talking about? Position scientists as like almost infallible, detached, neutral, totally objective uh keepers of the truth. And um of course objectivity is still the goal but this attitude can drift into something unhelpful. Uh a sense that scientists must present themselves as certain above bias or emotionally removed from their work. Um the trouble is the moment that something changes new evidence appears a prediction turns out to be wrong. A coonian paradigm shift happens. People will feel misled. Trust crumbles. It's not the science that damages trust, but it's this performance of certainty. What we know now is that trust is built less through claiming authority and more through sharing our processes, being open about uncertainty, explaining why and how evidence evolves, acknowledging our values, our limitations, and our mistakes. So an attitude that fosters trust looks more like transparency and not just performative neutrality. If we can communicate in that way that is human and open and reflective, we give people a much sturdier reason to trust us if things go wrong or change. >> [snorts] >> So now I'm going to touch on a few communication principles that can help us now connect science to real people in real contexts and keep that foundation of trust. When we think about science communication or communication in general, we often default to what we might call a transmission model. So that's the idea that communication is basically a pipeline. You have an expert sender who is objective, who holds the power and they are passing information to a receiver and that receiver ought to be grateful and they are being helped by the sender and the job is to make that transfer as clean and accurate as possible. This is appropriate in some contexts, a news broadcast so on but this doesn't necessarily reflect how people actually make meaning. An alternative way to think about communication is the ritual model. Here, communication is about creating a shared understanding and shared culture through dialogue and through participation with your audience. It's a two-way process or a three and a four-way process. It acknowledges that people already have experiences, values, and worldviews that shape how they interpret in information and that they themselves have valuable contributions to science and to the process of knowledge making and learning. We want people to participate in a conversation that builds a common frame of reference and that can be crucial in science outreach because most of the time we're trying to help people connect new ideas to the world that they already know when we're informing them. [snorts] This can involve practices like co-creation where the stakeholders or intended audience contributes to the direction or the production of the materials that you're using. It could involve focus groups or surveys that help inform you. And it can include things like citizen science. This attitude can make communication more respectful. Um bear with me. Uh effective, engaging, and ultimately more trustworthy. On top of this, culture shapes uh motivation and understanding. Uh this is something quite close to me. It's something I studied at university. Um, culturally responsive pedagogy or communication is a way of teaching and communicating that recognizes that understanding and motivation is not universal. People don't absorb information the same way because their upbringing, their community, their schooling, their cultural background all shape what feels relevant and engaging or how they respond to authority. Even [snorts] we can draw this back to the received view that we talked about before of a scientist. Uh this received view is realistically dominated by a white western ideal of uh disinterestedness, politeness, rigidity. And this uh this attitude in educational settings might not make sense for uh students and children from cultural backgrounds where say dialogue and expression are much more valued. Culturally responsive communication means acknowledging the backgrounds that people come from and adapting how we present science to make it resonate. When we recognize those differences and we build them into our approach, we foster intrinsic motivation. People engage because it speaks to them, not just because we're telling them to and not just because they need to pass a test. This actually gives you really exciting opportunities to be a lot more creative. You can think outside the box. For my master's thesis, I explored how philosophies and practices from hip-hop culture because I'm a massive hip-hop head like co-eing or or rap battles and ciphers could be used in a science education setting for children in London schools. That was my focus. Um, examples of this is the science genius rap battles which I've got here are still on the frame and I would really encourage you to look it up because it's really cool. But the goal is resonance, making people feel seen and included in the process of learning and understanding and knowledge sharing. And and when you do that, they're far more likely to engage, ask questions, and and take ownership of their learning. So, we've talked a little bit more hypothetical and philosophical. Uh in this second half of the talk, I'm going to talk from principles to practice. um how do we actually adapt our scientific ideas uh with a focus on non-scientific audiences and what tools can we use? When we talk about adapting science for non-speists um the instinct is to jump straight into simplifying your language um summarizing but the first step is of course to understand who you're speaking to. Different audiences care about different things. uh a classroom of teenagers, community groups that are worried about local pollution, policy makers, patients, parents, they all have different motivations, different anxieties, and they're listening to you for different reasons. If you don't understand those reasons, your message might be perfectly accurate. It's not going to be heard. So before crafting anything, you want to ask what are they interested in? What are their values? What do they already know and and don't know? What ex often they know a lot more than you think. Um what experiences are they bringing into the room? This includes a cultural background, lived experience, familiarity with science and their relationships to institutions, for example. A lot of the things that we've spoken about so far. And [snorts] of course, you won't know these things right up front. Part of the job is to get closer to your audience. That could mean talking to organizers, reading comments, finding forums, looking at what's being discussed in the news, running a focus group, a poll. Even small bits of insight can change the way that you frame a message. And once you understand where people are starting from, you can start shaping your message and content to their needs. You will learn as you go, and you should always seek feedback wherever possible. So, let's be more specific. Figuring out exactly what you want your audience to take away from this. Um, what's the important finding or the key implications? A useful thought process for me is to think, uh, what information can I remove from my piece of communication while still getting the message across? Can I remove more? And if I can, I should. We've found that technical terms can sometimes activate experts. I'm thinking of my experience on social media, but on the whole, plain language makes your work accessible to broader audiences, and that's probably your goal if you're talking to the public. Again, I highly recommend adding context and explaining the relevance of research to your audience and why they might care about it. That's how you get their attention. And when you work in research, uh I mean I don't work in research, but I work with researchers. And I think it can be easy to develop blind spots to jargon and to meta concepts. Um a meta concept if you're unfamiliar um is essentially an umbrella concept that encompasses a lot more technical knowledge that you as a scientist might take for granted. Stress is the good example. Stress tends to have a quite technical and precise meaning in research as something mechanistic and tightly controlled such as temperature or physical pressure. To a lay person, stress is just having a bad day. If you said you were applying stress to a cell, that might be quite confusing to a non-scientist. Don't be afraid to use metaphor and analogy. uh for audiences that don't have the technical knowledge, these are absolutely vital tools for making information accessible and relatable. I think there can be a fear of sacrificing accuracy or being misleading. So, you do have to be careful. But this is where it's really important to be so clear on what your message is, what you want to get across. As long as you are still communicating the important information that you want them to take away with them, the details might not be important. So, I'm going to give you a little example here. This is an impact statement from an EL life research paper linked there. Uh, I'm going to take you through a very, very simplified example of how I might approach um rephrasing this for a lay audience. I obviously write for social media, so I'm always writing in very short form content like this. This is by no means a comprehensive approach to uh plain language summaries but is simply demonstrative of some of the simple language changes that you might take for granted day-to-day. So we have here uh an impact statement. I'll read it. Fitness constraints on the HIV envelope protein are highly similar in humans and Reese's Macaks emphasizing the utility of macac models of infection and antibbody development. Now, I've highlighted here some terms that I could quickly substitute to help someone understand this paragraph. Uh, in pink, I've highlighted fitness and models. Uh, I would consider those to be meta concepts. They're simple words, but they carry a lot of meaning to researchers that a lay person probably doesn't have access to. For example, fitness in this context has very specific evolutionary implications around survival around reproduction. To a lay person, fitness just means how strong or energetic they are. So, it's a bit misleading. While it's more precise and specific for you, for a lay person, it's it's misleading. [snorts] HIV envelope protein that is obviously jargon. And in green, I've just highlighted some things that I would just rephrase for the sake of being more readable. It's not that they're not understandable, but they're just written in such a way that is less common in simple language. Here's specifically how I'll do it. I won't read all of these out, but you'll notice in some of these I'm choosing before between metaphor and explanation here. It's kind of whatever works best, whatever you're comfortable with. So, for the HIV protein, I've explained that in quite literal terms cuz it's kind of complex and I need to be specific. But for fitness, I've used kind of a metaphor. I've called it evolutionary rules. It's not totally precise, but it says what I need it to say. So this now becomes the parts of HIV that help it enter cells follow similar evolutionary rules in humans and macaks emphasizing how useful macaks are as tools to research the immune system. I think as researchers we want to be incredibly precise but don't be scared to sacrifice that precision when you are communicating to late audiences. Think twice about how technical something really needs to be to get that across. For example, I could probably simplify this further, the bit in blue. I could probably just make that HIV molecules or just HIV uh because that's not necessarily needed for the core message. The core message here is that similarities in HIV evolution across species helps immun immunological research. effective psychom and spotting all of these sort of uh blind spots that you have to language takes a lot of practice, takes time and again takes a lot of feedback. You should be passing these to to people. This is something that I used to do when I started at E Life. I would show everything I wrote to my housemate to see if she understood what I was talking about. It's really good to get that feedback on things like this. A final piece of advice that I'm going to give you for this section uh is around transparency. I'm sure hopefully we all understand as scientists that a level of uncertainty is inherent in all research. Uh we've talked about it in our philosophy of science section, but it is particularly important for papers that haven't been reviewed or reviewed or revised like preprints. It's also important for fostering trust. A lot of the public don't have this level of insight into the scientific or publishing process. So, it's important to be clear about the certainty and the limitations of research shared. It's tempting to lean into findings that you're excited about, but be very careful about not overstating or sensationalizing. Explain the limitations as best you can and indicate when you or the authors of something are speculating. You could talk about whether something is a preprint, if it's contextually appropriate, whether it's been reviewed or not, and then what that means if you want people to sort of start to understand the scientific process. Uh the examples that I've got on the right here, you probably already know. These are our E-Life assessments at the top of each paper. Things like this have offer a really useful tool for talking about the strengths and the limitations of research in a very simple and standardized way. These concepts are a lot to communicate, especially if you're doing short form communication or when you just really want to focus on a a learning or or a specific message from the topic. But even simple things like just avoiding definitive language can help. So, we've talked about writing, but when I chatted to some of you last month, uh I know some of you wanted to learn about visualization. We have a great webinar on this. I've linked it here so you can see. Um, and I've summarized some tips from it. In science communication, visuals are not decoration. They are tools for meaning making. A strong visual does a couple of things at once. It's going to simplify complexity and it's going to give people an intuitive sort of foothold into an idea. [snorts] Diagrams are something that I found incredibly useful when teaching as part of the process. I really like to create diagrams with my students step by step. Uh it was a way of showing a process having having them build it progressively with you kind of mimics the process that you're trying to show them and walking through concepts and and and encourages them to build their own styles of learning and understanding by kind of pulling together the information themselves and making those connections. So a lot of the principles from writing still apply here with visualizations i.e. Keep things simple and focused. Release yourself from the expectation of accuracy in favor of meaning. One of the most powerful ways to visualize science is to lean on metaphors. Uh especially when you're working with children because they have a much narrower frame of reference. If you can connect a new concept to something familiar like lock and keys for receptors, traffic flow for signaling pathways, you immediately reduce the cognitive load on the viewer. Uh remember these metaphors are going to be culturally informed. It's another instance that emphasizes the importance of culturally cultural sensitivity. What can you compare this concept to that actually resonates with your specific audience? What do they know about? Another basic move is to replace technical objects with icons. Um, so for a public audience, you often don't need um, for a public audience, you don't often need like a full molecular structure of a protein. You just need a shape or a symbol that stands in for it. Less detail gives late audiences less to process. Try visually thinking in terms of storytelling. Uh, this kind of goes back to what I was saying about creating images as well. Creating diagrams with my students. Think about how you present processes um and timelines with your images. You might want to use a before and after. You could use a sort of single stepwise sequence, multiple iterations that build in detail. These things don't all need to sit in one diagram as well if there is a lot to communicate. Zoom in to elaborate on a key section. Break things apart. Show different stages across multiple frames. as long as you keep a sense of continuity and directionality. [snorts] And above all, remember that your audience might not have the same mental library as you. If a visual only makes sense to the people who already know the field, it's obviously not doing what you want it to do. Get feedback. [snorts] The goal is not to just fill a space with something pretty. When you have something to communicate, you want to create a coherent and focused message. That means every line, arrow, label, color earns its place. If a detail doesn't directly support understanding, you can probably let it go. [snorts] Simplicity doesn't mean babying, though. It means removing obstacles so that your audience can focus on what matters. You can always add captions uh or short notes if it will help orient your reader or add some context. Most people don't comprehend and pass numbers as well as we might think. People struggle with that quite a lot. So try and keep your stats and your numbers to a minimum unless they are really central or uh striking and surprising. And finally, iterate. Show your visuals to someone who doesn't work in your area. If they misinterpret it, that tells you something needs adjusting. The audience isn't wrong. Asking for feedback early is going to be the most efficient way to improve clarity and and keep learning. And that applies across the board really. More specifically, a consistent visual system makes it easier for people to follow along without thinking about it without the need to constantly reinterpret what they're seeing. So, use the same fonts, icons, color themes, and style throughout a single piece of communication. Sans serif fonts, so those are the ones without the little flicks on them, are generally clearer on screens, uh, easier to read, and um, changes in the size or weight of your text creates a hierarchy. They tell the viewer what to read first. This seems obvious, but it's important. Uh, never stretch text. You can see this in the example on the right there. Never stretch text. Distorted type instantly looks untrustworthy, even if we can't quite articulate why. Whites space is going to be a really powerful tool. Uh, whites space just means the empty areas around your text and your images. These are the gaps, margins, general breathing room around different features. It's not wasted space. Don't just fill your space. It guides a viewer's eye. It separates ideas clearly, and it stops the page from being too crowded. Using it well can make even complex visuals feel very simple and approachable. And if a a page looks crowded, it's confusing. It's overwhelming, and it's just hard for a viewer to think about what they're seeing. And it might seem obvious, but think about direction. Most people, depending where you're from, of course, we must think about culture. uh intuitively read left to right, top to bottom. So use that flow. Think carefully about shape and size. They can do a lot of communicative work. As we've said with text, larger objects naturally draw attention first. So size hierarchy is a simple way to emphasize what's important. If you're representing quantities like the example on the top right here, length is much better than area wherever possible. People intuitively compare lengths, but area is surprisingly different to judge accurately. [snorts] Color is a hugely loose useful tool, of course. Uh it allows you to group elements and concepts, represent values, separate information, stick to intuitive conventions when you can. Uh green for growth, blue for cold, and so on. Let your colors have a meaning that is consistent throughout your piece of communication. Uh color isn't always going to be dependable. Um it might depend how your work is displayed. Many people have color vision differences. Um and you might be printing out in grayscale. Um you can pair color with labels. You can use patterns. You can use different outlines. Um and if your graphic is going to be seen in black and white, you can use shade to differentiate values. You know, not using color is difficult for something like a a heat map or something, but shade means that colors have more or less black in them, so they translate to a grayscale better if that happens. Now, let me take a joke. Now, uh, a lot of you had questions last month about how to foster collaboration. This is a really tricky and thorny topic. It's one of those aspects where your work and efforts can often go unrewarded. you rely on a lot of hard work and sometimes luck. But here again with help from Shane, so thank you and some of El Life's staff who regularly collaborate outside of the or I've got a few practical tips that hopefully help and encourage you. Effective outreach begins with how you show up as a person. It can take a lot of effort. As I said, you don't always get returns. It's hard work, but you will only ever get out what you put in. Uh it's not all about your accolades. It's like you don't you don't need to have so many things to your name. Just being approachable and genuine opens people up and makes them want to work with you. One of the easiest ways to build connections is to simply signal your presence and your interests wherever you have the chance. Even in, for example, calls like this. Let people know what you're working on, what you care about and how they can reach you. Uh if you're heading to a conference or to a meeting, post about it, mention it in advance so people have a reason to find you. Share your contact details if you're comfortable and make your interests visible in small ways like your email signature. All of these like simple tiny cues are things just just increasing your chances of being picked up and gives people opportunities to engage with you. And a a really important thing is underpinning all of this. Know your value. This is something that I struggle with. I hate networking. But if you're at an event or part of a group like this, you belong in the space. You either are bringing some expertise or you have something to learn. And both of those are completely valid reasons for you to be there and you shouldn't be scared to talk to people. The next step is actually reaching out. Our staff get requests to speak all the time and you just never know who will say yes. So cast your net wide, maybe wider than feels comfortable, senior people, people you admire, people outside your field. It's just worth having a go. A great tip is to look for community or engagement teams like the one you're working with now uh inside organizations. They often act as connectors and they can point you to exactly the right person or they will probably have resources to support you. When you write to somebody if you're emailing or reaching out on LinkedIn, keep it concise, keep it personal so it's not spammy and just a few lines that make it totally clear what you're asking from them and why. Show that you've done a bit of research so you're not looking like spam. Say something specific about why they and not just anyone can help you. Frame [snorts] the invitation in a way that empowers them. What impact could they have? Why would their involvement matter? That will make them want to help you. Uh with some extra research as well, you might be able to find and and show them how your project or request fits into their goals as well or tailor it. And finally, there's a myriad of reasons why someone might not respond. Uh, it's worth being persistent and following up, but obviously know when to stop. Silence usually means that you maybe need to try a new angle or try a different person. Once you've got people involved, could be a a full-on project collaborators, um, a focus group, speakers for an event, and so on. [snorts] How do you nurture those collaborations? How do you pull off a project? A good starting point is to recognize the skills, experience, and assets that are already in your team or community before you outsource this. I didn't write it here, but I think Shane, you said this is assetbased something. I'll let you fill in. >> Uh, yeah, asset based community management. >> There we go. Asset based community management. Thank you. Um, doing this makes the people that you've already got feel valued and that what they bring is noticed. uh make participation easy for the people you've got. If you can take on the logistical load of scheduling, of admin, of facilitation, it's going to remove barriers and gives people space to contribute meaningfully. Granted, this is hard and a lot of work. Co-creating goals and content is ideal. Uh it means actively working together with participants on the outcomes of the work that you're doing in contrast to just telling them what you want. Think ritual, not transmission communication. >> [sighs] >> is often a lot more effort than just doing things yourself. But when people have a genuine stake in shaping the work, they naturally become its champions. They're going to advocate for it because it's also theirs. And that's when communication stops being a task and becomes a shared pride. So now we're getting a bit more specific again. I'm moving into my own expertise here. Most of the advice you've heard uh so far applies to social media. I'm thinking transparency, clarity, simplification, visualization. But I I I've got a few specific tips on getting started in social media from my experience at EIFE. There are many many many challenges with social media these days. Uh one of the most significant ones over the last few years, particularly with takeovers like Twitter from you know who is an increasingly pay-to-play style environment. This means more and more features like advertising visibility and even whether you can post certain types of media are only available to you if you pay. that's not accessible. Most of the major platforms favor certain types of content that keep people on the site. So, if you're posting links to your work elsewhere, the algorithms quite literally will hide your posts from more people. It means social media is worse from a traditional marketing perspective. It's hard harder and harder to get people to see what you want them to see. [snorts] At El Life, we've actually refocused some of our goals on social media to be more about engagement than getting readers to our website. Um, it's just not really working. I think generally speaking, it's important to focus more on the types of interactions that your audience wants to have versus what you want them to do. Uh it means you have to work more in within the constraints placed by these self-interested platforms. But you could say that for most things, [gasps] it can be hard to get data insights into performance uh of your posts. These are often payled and frankly it's really difficult to make inferences from those insights. Don't stress it. In my experience, performance on social media can be quite random. Um, the takeover of Twitter, generally increased polarization has meant that a lot of people's social media uses going down and they are dispersing across alternative channels, make it a lot harder for you to reach people in one go. And finally, creating interesting and quality content takes time. You sometimes have to find the workarounds to be more efficient, and that can mean making trade-offs. can't do everything and that is completely okay. So, what can you do? Chances are you already have a social media presence, but if you're thinking of starting from scratch, how do you choose where? Uh, again, look at where your target audience is most active. There's loads of demographic information for free online if you just Google it, if you search it. Are there any community spaces that already exist? Maybe a subreddit, a Facebook group, individual accounts, popular hashtags like ECR chat. Take some time to familiarize yourself with the features of each of these platforms. See if there's one that best matches the way that you actually want to communicate already. Do you want to make video or text content? Do you want to engage in open dialogue? Places like Blue Sky and Twitter are really good for that. My biggest tip really is to experiment. And this goes for all science communication. As I said, a lot of social media can feel hit and miss. So just try new things and chase whatever works for you. We always recommend using visual media that's high quality, interesting and appealing at a glance. You can use some of your tips from before. And if you want to create it, find hooks that are engaging, that catch people's attention. Um, something punchy and interesting that's relatable or surprising, but be careful not to clickbait people. Don't over sensationalize. Don't mislead people. They will not like it if they feel like you're being dishonest, and you risk spreading misinformation. Recycling content can be a really useful way to balance uh the time investment you have. There might be multiple applications or findings in a single piece of research that you can talk about separately. There might be images and videos that you can use across different platforms. Perhaps you can resurface some research when it relates to current events or a new advance or discussion in the field. Point being, if you've spent creating a piece of work to explain your research, you can use that again and again and chop it and change it to keep it fresh and keep the attention going. Interacting with others on social media is one of the most effective ways to build visibility and create an engaged audience. It works a lot like networking in real life. Don't just post and walk away. Be ready to respond thoughtfully uh and do so in good faith. Um, you can also take the initiative and seek out conversations that are relative to your relevant to your field. Um, it lets your name be seen, helps you connect with communities that you want to reach. Tagging other you tagging other users can amplify this effect, whether to credit them, encourage them to share, or just to engage. Um, we found that tagging authors is often more effective than institutions because just they have more time. um they're more likely to respond, but be considerate. Don't be spammy, especially if you don't know them personally. Don't just expect their cooperation. Ask for it nicely. [snorts] And finally, remember that social media is usually an open space. Anyone could see or interact with you. Uh things can be taken out of context and misinterpreted. So, just be mindful and clear about how you're going to be interpreted by different people. So, [snorts] if you've got some research that you think is really important, you want to shout about it, what can you do to get some news attention, this is the final section today, and I've got some practical tips from our media relation media relations manager, Emily Becker. Um, you probably already know, but most institutions and journals will have a dedicated press team like Emily. Sometimes they'll be called communications, media relations, or marketing, or comms. Um, when you publish a paper, one of the institutions involved will likely have one of these. Their job is to help research reach the public, and they're usually delighted when researchers like you come to them prepared. What they need from you is simple. Start with a very concise email, just a few lines or a couple of short paragraphs that outline the findings, why they matter, and whether you're available for interviews. That's optional, but very helpful. Uh, it's not about writing a full press release at this point. It's just about giving them the raw materials so they can assess the potential and the news value easily. Uh you probably want to create a press kit. Uh that can help immensely. It just means having all of the useful information about your paper and to promote it linked in one place like a document or a downloadable file um or folder so press officers and journalists can access them efficiently. Try and include a plain language summary. It should spell out the key messages and why it's newsworthy. images, diagrams, clips that that help attract attention or explain things better. Think about what's visually striking to the general public. Um, you might want to include a short biography about yourself and your institution and other relevant contexts. [snorts] We really, really advise connecting departments if you've reached out to multiple uh, press offices. It lets them coordinate and be more strategic. And don't let this be an afterthought. If you know you want to promote your work, keep an eye out for good photos and images while you're doing the research. So, you might want to go beyond your internal press teams and reach out directly to journalists, especially want a bit more control over who sees it. Um, in this case, preparing your own press release is going to be important to include in your press kit. Um, I've linked a template from Emily here as well. Um, the hardest part is often finding the right contacts. Um, Emily says that you can start by looking at who has written about similar topics before. A quick news search can show you what outlets cover the same kind of fields. From there, you'd probably be able to track down a direct email address to a reporter or at least the broader science desk for that outlet. Um, if you can find a specific person, you can personalize your email by addressing them. um explaining specifically why they and not somebody else would want to cover this and it shows that you're not mass emailing and you're not being spammy and you might build a professional relationship going forward. Um a word of caution, not all outlets are equal. Some have a poor record with accuracy and sensationalism or ethics. So be selective. Don't owe your work to everyone who asks for it. And finally, aim high. There is no harm in trying major outlets. You just never know who's going to say yes. Many journalists rely on scientists reaching out. Even if it doesn't land, the worst thing they can say is no. And maybe you've built a contact contact for next time. So I will leave it there. Uh ultimately good science communication takes practice and inspiration. It's not about just simplifying the science. You want to strengthen connection, trust, and understanding. And if we approach people with openness, openness, transparency and clarity, that confirmation that follows, conversation that follows can be transformative.