Samira Hosseini's Linkedin Analytics

My 1st paper got accepted without ANY comments. But I almost didn't submit it! I was insecure, felt unqualified. I wasn't sure if it had a chance in a Q1 journal. But on 27 November 2013, I pressed Submit. 3 months later, I received the response, Straight acceptance, not even 1 comment, Only praise from the reviewers and editors. My biggest fear became my biggest victory. What's holding you back isn't skill. It's fear. Your fear of flaws & imperfections. Your fear of being rejected. Your fear of failing. But there's something bigger than fear, something that will bother you over time, something that'll hang in your heart forever. And, that's the "What if?" What if you trusted yourself? What if you took a chance? What if you aimed high? If you want to get those papers published in top journals in your field, and have me teach you how I did it, download my free 4-step guide: https://lnkd.in/eb5rGqht

You know what is even worse than a broken paper? The broken self-image of the author of the paper. Start again today. Begin anew. Begin by trusting yourself. Ask: if others have made it, why not you?

8 Types of Data Analysis 🗃️ Save this for later 1️⃣ Descriptive analysis: ➣Summarizes key characteristics of a dataset. ➣Uses measures like mean, median, mode, standard deviation, and ➣visualizations (histograms, bar charts) to describe data. 2️⃣ Diagnostic analysis: ➣Investigates the root cause of problems or issues. ➣Analyzes historical data to identify patterns. ➣Understand why things happened. 3️⃣ Predictive analysis: ➣Forecasts future outcomes or trends based on historical data. ➣Uses techniques like machine learning. ➣Relies on statistical modeling, and time series analysis. 4️⃣ Prescriptive analysis: ➣Recommends actions based on data insights. ➣Combines predictive models with optimization. ➣Suggests the best course of action. 5️⃣ Text analysis: ➣Extracts meaningful information from textual data. ➣Includes sentiment analysis, topic modeling, and named entity recognition. 6️⃣ Exploratory data analysis: ➣Uses visual and statistical methods. ➣Summarizes the main characteristics of a dataset. ➣Often, it is the first step in any data analysis project. 7️⃣ Causal analysis: ➣Determines cause-and-effect relationships between variables. ➣Goes beyond correlation to establish direct influence. 8️⃣ Social network analysis: ➣Analyzes relationships and interactions within a network. ➣Used to study the spread of information, identify influential individuals, and understand group dynamics. _________________________ 📌 This is Prof. Samira Hosseini. Researchers who took my training have published over 2,000 articles in top-tier journals, significantly raised their h-index, and advanced to top academic positions. Join my inner circle to ensure you don’t miss a single learning opportunity! Sign up for free: https://lnkd.in/eVNSihCM

"My efforts are not seen." "Am I really good enough?" "Do my papers add any value?" Is that what you whisper to yourself? The sole answer to your questions is YES. Fear and self-doubt have kept many amazing players out of the game. Don’t let it be you. Unless you believe that what you do is incredibly important, nothing will move forward. Let me share with you my perception of publication, which has drastically changed over time. As a junior researcher, it was a necessity. I checked off the boxes to grow in my career, to fulfill the KPI(s) and get a permanent position. Only when I began training faculty members, did I see publication in a different light. I saw many brilliant academics finally been seen, amazing ideas materialize and serve. I saw those with zero publications, even those close to retirement, grow to become chief editors, win international prizes, inspiring leaders, training others. These were not just publications. This path was sacred! How do you view journal publication? Do you enjoy the whole process? Is it a pathway to contribution? Or a dreadful obligation?

If you're dealing with qualitative data collection, this table will come in handy. ♻️ Save it for later. There are multiple methods for collecting qualitative data. Each has its pros and cons. Let's take a look at them: 1. Interviews: Pros: Deep insight, flexible probing, rich data, hypothesis spark, context ('why'). Cons: Limited generalization, researcher bias, standardization hard, time/resource heavy, replication tough. 2. Focus groups: Pros: Diverse views (fast), group dynamics shown, new questions, public views, efficient. Cons: Conformity/bias, moderator influence, individual views lost, limited generalization, privacy concerns. 3. Observations: Pros: Natural behavior, unconscious actions, context for quant, grounded theory, complex interactions. Cons: Observer bias, reactivity, causality unclear ('what' not 'why'), ethical issues, hard to control. 4. Document/Artifact analysis: Pros: Unbiased data, historical context, discovery insight, trend identification, cost-effective. Cons: Intent is unclear, there is potential bias in source, incomplete info, interpretation is challenging, and access issues. 5. Case studies: Pros: Deep understanding, new theories, illustrates processes, multiple data, rare events. Cons: Limited generalization, researcher bias, unclear causality (association not cause), heavy time/resource requirements, and difficulty defining scope. 6. Open-ended surveys: Pros: Broad views, theme identification, honest answers, fast collection, and quantifiable data. Cons: Limited depth, time-consuming, no probing, interpretation issues, literacy dependent. __________________ 📌 This is Prof. Samira Hosseini.  I've helped thousands of ambitious academics go from struggling with publishing papers in Q1 journals, limited visibility, and poor citation records to building a solid research trajectory and high 𝘩-index, gaining recognition & reputation, and positioning themselves as authorities in their disciplines. Book a call with me: https://lnkd.in/eraeb3Qg

The ability to wake up and start where you left off is a superpower. Can you jump out of the bed and get started immediately? Or do you have a hard time getting started on the tasks? Don't get me wrong, I have those days when I question my existence, When I feel like a failure, my own worst judge, When I tell myself, it's harder than I thought, Or when I ask myself, "What's the point?" Here is a reminder for both of us 👇 You cannot expect to achieve anything significant in life if you do not commit to your ONE THING for 4 straight hours in a row. And, here is a bigger reminder for you and me, my friend 👇 Life is not measured in weeks, but in decades. What seems to be a complete nonsense deal of progress now, can lead to a massive breakthrough in a year from now. Keep going!

What you see as failure might look like success to someone else. You never know who’s quietly watching, admiring your persistence, your grit, your every move. Keep walking your path. Keep inspiring.

'Reject and resubmit' is an indirect major revision. If they didn't want your paper, they would reject it. Journals benefit from this strategic move. The more they reject, the higher their reputation goes in terms of indexing metrics. Got a 'Reject and Resubmit' answer from a journal? Treat it as a Major Revision! Get back to the journal ASAP. Never let a revision sit too long, even if you're not given a deadline. Stick the dough in the oven while it's hot. 🥖 🍞 ___________________ Don't take longer than: Minor revision → 1 week Major revision → 1 month Reject & resubmit → 1 month The world stops when you receive a revision! That means anything else is a secondary task. ___________________ If the comments in the 'Reject and resubmit' decision are LITERALLY impossible to address, consider making another submission. ____________________ Don't give in easily. Don't take the easy route. Be Brave to make the impossible possible.

4 lessons I learned from my 4 cats which you can apply to your academic life! ➟ DO NOT MOVE your eyes from the target. Have you ever seen a cat spotting a bird? Gosh, they are hyper-focused. ➟ SET CLEAR boundaries! Cats are no people pleasers. Try to do them wrong & you'll regret the consequences. ➟ Never hesitate to ask! [and be a little entitled] So much is denied to us, simply because we didn't ask! Know your place. Claim your throne. ➟ and Aim HIGH! Like really really high. Trust yourself. You have what it takes to jump that high!

"Maybe I am not good enough" must be removed from humanity's memory. You're more than good enough as long as you put your best effort into each day. Period.

Afraid of arriving at misleading conclusions? Don’t second-guess yourself!   A strong understanding of statistical tests is crucial for interpreting findings.   Check out this FREE article which highlights the most frequently used tests and it helps you in choosing the best one for your project.   Here are some important points to get you started: 👇🏻   ✺ To select a Statistical Test: → Define the research question and null hypothesis. → Choose the appropriate test based on the type of data (e.g., continuous, binary, categorical) and study design (e.g., paired vs. unpaired). → Determine the significance level and decide on a one-tailed or two-tailed test.   ✺ The type of measurement scale (continuous, categorical, binary) influences the choice of statistical test. For example, continuous data may require parametric tests, while categorical data may require non-parametric tests.   ✺ Statistical tests must account for whether data points are paired (e.g., same participants at different times) or unpaired (e.g., different groups).   ✺ There are two types of errors in statistical testing: →Type I error (false positive): Rejecting the null hypothesis when it’s true. →Type II error (false negative): Failing to reject the null hypothesis when it’s false.   ✺ Two key factors for selecting a test are: →The scale of measurement (continuous vs. categorical). →The study design (paired vs. unpaired).   ✺ Here are some common tests and their applications: → Fisher’s exact test and chi-square test for categorical data comparisons. → T-tests (for normally distributed continuous data) and non-parametric tests for ordinal or non-normally distributed data.   ✺ Methods like survival time analysis (log-rank test) and correlation analysis (Pearson and Spearman) are used to examine specific types of relationships or time-based outcomes.   ✺ Not all studies require statistical tests, especially descriptive studies or those based on logical reasoning.     Statistical tests are not always conclusive and should be used carefully to avoid drawing misleading conclusions.

No payment required! Google is offering AI courses with certification. Here are 12 courses to help you learn AI in 2025! →  Generative AI for Educators – Use AI to personalize learning, boost engagement, and simplify admin work. Course link: https://lnkd.in/ezc2xRT5 →  Introduction to Large Language Models – Learn how LLMs can transform research and business. Course link: https://lnkd.in/eQtWjxx3 →  Integrate Generative AI Into Your Data Workflow – Optimize data analysis with AI-powered automation. Course link: https://lnkd.in/eNuycDhr →  Google Cloud Big Data and Machine Learning Fundamentals – Master the AI lifecycle with Google Cloud tools. Course link: https://lnkd.in/eyPNRjhr →  Introduction to Responsible AI – Understand AI ethics and how Google applies them. Course link: https://lnkd.in/e-BSPMDb →  Smart Analytics, Machine Learning, and AI on Google Cloud – Hands-on training for AI deployment. Course link: https://lnkd.in/e4S8x7WQ →  Introduction to Machine Learning – Learn how AI makes predictions and decisions. Course link: https://lnkd.in/eyqkAwdN →  Applying AI Principles with Google Cloud – Implement ethical AI in real-world applications. Course link: https://lnkd.in/etPUp4e9 →  Understanding Machine Learning – Build a solid foundation in AI concepts and model training. Course link: https://lnkd.in/eA6SRrKN → Introduction to the Cloud – Explore cloud computing and data management basics. Course link: https://lnkd.in/e34H_GGb →  Understand the Basics of Code – Learn how coding works and why it matters. Course link: https://lnkd.in/eCrTy7eQ →  Prompt Design in Vertex AI – Create effective AI prompts for smarter marketing. Course link: https://lnkd.in/e8jTQdQK No more excuses. Let's jump into it! ♻️ Repost to benefit others. ______________________ 📌 This is Prof. Samira Hosseini. I've helped thousands of ambitious academics go from struggling with publishing papers in Q1 journals, limited visibility, and poor citation records to building a solid research trajectory and high 𝘩-index, gaining recognition & reputation, and positioning themselves as authorities in their disciplines. Book a call with me: https://lnkd.in/eraeb3Qg

I’m considered a productivity guru by many. But now and then, I catch myself being lazy. Laziness doesn’t always mean doing nothing. It can also look like: → Avoiding tasks out of fear → Postponing and endlessly delaying → Staying busy with things that don’t matter → Misplacing priorities and misusing resources To me, these aren’t just side effects of inactivity. They’re the direct result of not taking the time to focus, Identifying and sparing time for what truly moves the needle. Let’s correct ourselves today, here and now. Let’s lean into these Japanese techniques, filled with wisdom: 1️⃣ Ikigai – Discover academic purpose by aligning research with passions, talents, societal needs, and career goals. Instead of choosing a research topic just because it's "trendy," identify a research area that aligns with your passion and how you want to add value to the world. 2️⃣ Hara Hachi Bu – Academics hardly get enough time to exercise. Add to that poor eating habits, and it’s a recipe for disaster. Pay attention to hunger cues and stop eating when 80% full. Practice mindful eating to maintain energy and focus for optimal academic performance. 3️⃣ Kaizen – Embrace continuous improvement through small, incremental changes in research and learning habits. Have an eye on macro goals but work within the micro goals agenda. That makes massive progress a reality over time and consistency. 4️⃣ Ganbaru – Persevere through challenges with determination and a strong will to achieve academic goals. Never, ever give up. You don’t need motivation—you need a reason strong enough to get you going, no matter how hard the circumstances might be. 5️⃣ Wabi-sabi – Find beauty in imperfection and embrace the learning process. View research as an iterative process. Embrace the inevitable imperfections in work. Refine your approach and ultimately produce stronger research. 6️⃣ Shinrin-yoku – Immerse yourself in nature to restore focus, reduce stress, and enhance creativity. “All truly great thoughts are conceived while walking.” ― Friedrich Nietzsche 7️⃣ Kakeibo – Utilize mindful budgeting to manage resources effectively and support academic endeavors. Have you ever heard of the toothpaste theory? At first, when you have a full tube, you may take too much out for every round of brushing. You may throw a bit of paste around and hardly use 30% of what you took out. But when the tube is nearly empty, how mindful you become of each piece! Let’s start with that same mindfulness from the very beginning when resources are plenty. 8️⃣ Shoshin – Approach learning with a beginner's mind, developing openness to new ideas and continuous intellectual growth. Let the child-like curiosity stay with you. There is a profound joy in discovering the world around you. __________________ 📣 I am an accredited coach by the International Coaching Federation. Book a call with me if you find yourself feeling stuck: https://lnkd.in/eraeb3Qg

This is what’s wrong with academia these days! 😡 $500–$1000 USD for each paper I sneak in as an editor!!! Note that this person is not a random middleman. He’s a professor officially affiliated with a university. See my response in the comment section!

"Academia Hates Pregnancy!" The “baby penalty” is a proven career risk. A recent article by Alicia Andrzejewski published in The Chronicle of Higher Education describes how academia steals the joy of pregnancy. Pregnancy discrimination is widespread in academia. ► Only 27% of academic mothers in sciences achieve tenure. ► 70% of tenured male professors have children. ► But, only 44% of tenured women have children. ► Women fear announcing pregnancy, especially pre-tenure. Discrimination intensifies at the intersections of identity. ► Black women, despite being only 14.3% of the female workforce, filed 28.6% of pregnancy-discrimination charges. ► Pregnant women of color received lower teaching evaluation scores. The culture of hostility is real. ► Anecdotes describe faculty shaming or dismissing pregnant women. Examples include: ► “I am so disappointed in you” said to a visibly pregnant academic. ► Claims that hiring “women of child-bearing age” reduced department productivity. ► A senior academic expressing inability to relate to having a second child, implying it’s a professional liability. Academics report anxiety, overwork during postpartum, and inability to enjoy pregnancy. Why? Due to career fears! This is a serious issue that needs to be addressed. Prior to that, however, let's raise awareness on the topic. ♻️ Repost to help colleagues. ___________ The link to the article is in the comment section.

Be mindful of your collaborations! A retraction case from Johns Hopkins University! 👇 I always encourage collaboration, joining forces to give strength to projects. But let's also talk about the dangers of collaboration, Fabricated or misused data you're not even aware of, Little alterations here and there, you may not detect. This is one example: two affiliations, two corresponding authors, and none responded to the editor. a disaster... Choose your collaborators wisely. As the corresponding author, it's your duty to: - Ask for the origin of the obtained results. - Check the collaborators' past publications. - Show thoroughness in all steps of a project. Here is the retraction note: "An investigation conducted on behalf of the journal by Elsevier's Research Integrity & Publishing Ethics team found image duplication and alteration issues, with two images in Figure 5e being reused, recoloured, and stretched. The authors were requested to explain the duplication and alteration in Figure 5e but were unresponsive. The Editor has lost confidence in the findings of the article and has determined that it should be retracted." And the link to the article: https://lnkd.in/eb7m2BSF ________________ P.S. Retractions are more harmful than you imagine. According to some studies, it typically means the end of one's scientific career. ________________ 📌 This is Prof. Samira Hosseini.  I've helped thousands of ambitious academics go from struggling with publishing papers in Q1 journals, limited visibility, and poor citation records to building a solid research trajectory and high 𝘩-index, gaining recognition & reputation, and positioning themselves as authorities in their disciplines. Book a call with me: https://lnkd.in/eraeb3Qg

I didn't ask for a raise. Felt awkward to ask. Didn’t apply for a promotion. Felt unqualified. Held back from launching my program. What if I failed? Then I watched others, less experienced, move ahead. Not because they were more talented. Not because they were more qualified. But because they did what most of us hesitate to do. They showed up. Talked about their work. Submitted before they had all the answers. Applied before they felt prepared and got results! Success doesn’t always belong to the smartest person in the room. It belongs to the ones who take action even if they feel embarrassed. Speed is your only weapon against self-doubt. Act before your mind talks you out of it. You’ll gain more from doing than from over-preparing. This is the shortcut you’ve been looking for. 👆 To every academic holding back: Fear will keep you small. Embarrassment passes. Regret is what stays. Choose action. Repost ♻️ to inspire. ________________________ 📌 This is Prof. Samira Hosseini. I’ve trained thousands of researchers to publish over 2,000 articles in top-tier journals and boost their h-index. Download this free guide to access my proven 4-step strategy for publishing in Q1/Q2 journals: https://lnkd.in/eb5rGqht Your success starts here!

"Even if you're on the right track, you'll get run over if you just sit there." Move ... And remember, Not every movement is progress. Moving in circles won't get you there. Move forward ...

You either go down that track or this! No wonder my PhD friends are single.😅

What is she holding in her hands in the 1st revision? A coconut? 😅