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Last modified by Robert Schaub on 2026/02/08 08:32
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edited by Robert Schaub
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To version 1.3
edited by Robert Schaub
on 2026/02/08 08:32
Change comment: Renamed back-links.

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1 -FactHarbor.Organisation.WebHome
1 +Archive.FactHarbor 2026\.02\.08.Organisation.WebHome
Content
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5 5  == 1. Purpose ==
6 6  
7 7  Understanding who benefits most from FactHarbor helps us:
8 +
8 8  * **Product Development**: Prioritize features that serve core user needs
9 9  * **Marketing**: Communicate value effectively to target audiences
10 10  * **Partnerships**: Identify and cultivate strategic relationships
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17 17  === 2.1 Journalists & Newsrooms ===
18 18  
19 19  **Profile**:
21 +
20 20  * Working journalists at news organizations (local to international)
21 21  * Fact-checkers and verification specialists
22 22  * Editorial teams producing investigative or political content
23 23  
24 24  **Core Needs** (from User Needs documentation):
27 +
25 25  * **UN-4**: Fast social media fact-checking (≤15 seconds to initial verdict)
26 26  * **UN-14**: API integration into professional workflows
27 27  * **UN-5/UN-6**: Source provenance and publisher reliability tracking
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28 28  * **UN-7**: Evidence transparency for editorial review
29 29  
30 30  **Key Pain Points**:
34 +
31 31  * Time pressure with breaking news and viral content
32 32  * Need to verify claims quickly without sacrificing accuracy
33 33  * Difficulty tracing claims to original sources
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37 37  FactHarbor provides structured, scenario-based analysis that reveals **how** conclusions are reached, saving time while providing the context needed for accurate reporting.
38 38  
39 39  **Success Indicators**:
44 +
40 40  * Reduced time spent on claim verification
41 41  * Ability to cite FactHarbor analyses in published work
42 42  * Improved editorial confidence in complex stories
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44 44  === 2.2 Researchers & Academics ===
45 45  
46 46  **Profile**:
52 +
47 47  * University researchers (political science, communications, media studies)
48 48  * Think tank analysts
49 49  * PhD students studying misinformation
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50 50  * Data scientists working on verification systems
51 51  
52 52  **Core Needs**:
59 +
53 53  * **UN-7**: Complete evidence transparency
54 54  * **UN-9**: Methodology transparency (auditable reasoning)
55 55  * **UN-13**: Ability to cite FactHarbor verdicts in academic work
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56 56  * **UN-15**: Verdict evolution timeline (how assessments change with new evidence)
57 57  
58 58  **Key Pain Points**:
66 +
59 59  * Existing fact-checks are methodologically opaque
60 60  * Need structured data for quantitative analysis
61 61  * Difficulty comparing how claims are assessed across sources
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65 65  FactHarbor provides **transparent, structured methodology** that can be cited, analyzed, and built upon. The Evidence Model approach creates reusable data for academic research.
66 66  
67 67  **Success Indicators**:
76 +
68 68  * Academic papers citing FactHarbor methodology
69 69  * Researchers using FactHarbor data in studies
70 70  * Methodology validation by academic institutions
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72 72  === 2.3 Educators ===
73 73  
74 74  **Profile**:
84 +
75 75  * University professors (media literacy, critical thinking, journalism)
76 76  * High school teachers (civics, social studies, media studies)
77 77  * Librarians and information literacy specialists
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78 78  * Corporate trainers (media literacy programs)
79 79  
80 80  **Core Needs**:
91 +
81 81  * **UN-3**: Article summaries with FactHarbor analysis for teaching materials
82 82  * **UN-8**: Understanding disagreement and consensus (why experts differ)
83 83  * **UN-9**: Methodology transparency for pedagogical purposes
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84 84  * **UN-7**: Evidence transparency to teach source evaluation
85 85  
86 86  **Key Pain Points**:
98 +
87 87  * Fact-checks don't show reasoning process for teaching
88 88  * Hard to teach critical thinking with black-box verdicts
89 89  * Need tools that demonstrate **how** to evaluate claims
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93 93  FactHarbor teaches the **process** of evidence evaluation, not just the answer. Students see explicit assumptions, multiple scenarios, and how confidence levels are determined.
94 94  
95 95  **Success Indicators**:
108 +
96 96  * Educators integrating FactHarbor into curricula
97 97  * Student engagement with evidence exploration features
98 98  * Educational institution partnerships
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100 100  === 2.4 Policy Analysts ===
101 101  
102 102  **Profile**:
116 +
103 103  * Government policy advisors
104 104  * NGO research staff
105 105  * Legislative aides
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106 106  * Regulatory analysts
107 107  
108 108  **Core Needs**:
123 +
109 109  * **UN-2/UN-3**: Context-dependent analysis (claims true under some conditions, false under others)
110 110  * **UN-8**: Understanding why reasonable people disagree
111 111  * **UN-1**: Trust assessment with explicit confidence ranges
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112 112  * **UN-17**: In-article claim highlighting for briefing documents
113 113  
114 114  **Key Pain Points**:
130 +
115 115  * Policy questions rarely have simple true/false answers
116 116  * Need to understand stakeholder perspectives and their evidence
117 117  * Difficulty synthesizing information from multiple sources
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121 121  FactHarbor's **scenario-based analysis** explicitly maps how conclusions depend on assumptions, enabling policy analysts to present balanced, well-sourced briefings.
122 122  
123 123  **Success Indicators**:
140 +
124 124  * Policy briefs citing FactHarbor analyses
125 125  * Repeat usage for complex policy questions
126 126  * Feedback on improved briefing quality
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128 128  === 2.5 Content Consumers (General Public) ===
129 129  
130 130  **Profile**:
148 +
131 131  * Social media users seeking to verify viral claims
132 132  * Engaged citizens following news and politics
133 133  * People making decisions based on contested information
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134 134  * Anyone who has been frustrated by oversimplified fact-checks
135 135  
136 136  **Core Needs**:
155 +
137 137  * **UN-1**: Trust assessment at a glance (immediate visual understanding)
138 138  * **UN-4**: Fast social media fact-checking
139 139  * **UN-12**: Ability to submit unchecked claims
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140 140  * **UN-17**: In-article claim highlighting when reading content
141 141  
142 142  **Key Pain Points**:
162 +
143 143  * Don't trust fact-checkers' authority
144 144  * Want to understand reasoning, not just accept verdicts
145 145  * Time-constrained but want to make informed decisions
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149 149  FactHarbor shows **reasoning you can inspect**. Trust comes from transparent methodology, not authority. You can form your own judgment based on visible evidence.
150 150  
151 151  **Success Indicators**:
172 +
152 152  * User retention (return visits)
153 153  * Time spent exploring evidence details
154 154  * Claims submitted for verification
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161 161  **Priority**: HIGH (Tier 1)
162 162  
163 163  **Target Partners**:
185 +
164 164  * Swiss Broadcasting (SRG SSR, SRF, RTS, RSI)
165 165  * Major newspapers (Tamedia, NZZ)
166 166  * Regional news organizations
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167 167  * Digital-first news outlets
168 168  
169 169  **Partnership Value**:
192 +
170 170  * **For Partners**: Automated initial analysis saves journalist time; structured evidence for reader transparency
171 171  * **For FactHarbor**: Validation, use cases, credibility, potential funding
172 172  
173 173  **Engagement Model**:
197 +
174 174  * API integration for newsroom tools
175 175  * Embedded analysis widgets
176 176  * Co-branded fact-checking initiatives
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181 181  **Priority**: HIGH (Tier 1)
182 182  
183 183  **Target Partners**:
208 +
184 184  * IFCN (International Fact-Checking Network) members
185 185  * EFCSN (European Fact-Checking Standards Network) members
186 186  * dpa Fact-Checking (DACH region)
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188 188  * Full Fact (UK)
189 189  
190 190  **Partnership Value**:
216 +
191 191  * **For Partners**: Technology platform, scalability, methodology alignment
192 192  * **For FactHarbor**: Credibility, network access, ecosystem integration
193 193  
194 194  **Engagement Model**:
221 +
195 195  * Open-source technology sharing
196 196  * ClaimReview schema collaboration
197 197  * Joint methodology development
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202 202  **Priority**: HIGH (Tier 1)
203 203  
204 204  **Target Partners**:
232 +
205 205  * ETH Zurich / University of Zurich (Swiss, research collaboration)
206 206  * Duke Reporters' Lab (ClaimReview, Tech & Check)
207 207  * Harvard Shorenstein Center (network access)
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209 209  * Oxford Reuters Institute (journalism research)
210 210  
211 211  **Partnership Value**:
240 +
212 212  * **For Partners**: Research platform, real-world data, novel methodology to study
213 213  * **For FactHarbor**: Academic validation, grant access (Innosuisse), publications
214 214  
215 215  **Engagement Model**:
245 +
216 216  * Research partnerships
217 217  * Student thesis projects
218 218  * Co-authored publications
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224 224  **Priority**: MEDIUM (Tier 2)
225 225  
226 226  **Target Partners**:
257 +
227 227  * Knight Foundation (journalism innovation)
228 228  * Google News Initiative (fact-checking fund)
229 229  * Swiss Innosuisse (research/innovation grants)
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231 231  * Prototype Fund Switzerland
232 232  
233 233  **Partnership Value**:
265 +
234 234  * **For Partners**: Support innovative, transparent approach to misinformation
235 235  * **For FactHarbor**: Operational funding, validation, network access
236 236  
237 237  **Engagement Model**:
270 +
238 238  * Grant applications
239 239  * Progress reporting
240 240  * Impact documentation
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245 245  === 4.1 Unifying Frustrations ===
246 246  
247 247  All ideal customers share frustration with:
281 +
248 248  * Binary "true/false" verdicts that hide complexity
249 249  * Opaque methodology ("trust us" authority model)
250 250  * Lack of explicit assumptions and confidence ranges
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254 254  === 4.2 Unifying Values ===
255 255  
256 256  All ideal customers value:
291 +
257 257  * **Transparency**: Visible reasoning chains and methodology
258 258  * **Nuance**: Context-dependent truth (scenarios)
259 259  * **Independence**: Forming own judgment from evidence
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263 263  === 4.3 Decision Criteria ===
264 264  
265 265  When evaluating fact-checking tools, ideal customers prioritize:
301 +
266 266  1. **Methodology Transparency**: Can I see how conclusions are reached?
267 267  2. **Evidence Quality**: Are sources traceable and credible?
268 268  3. **Nuance Handling**: Does it acknowledge complexity?
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274 274  === 5.1 Awareness ===
275 275  
276 276  **How they find us**:
313 +
277 277  * Academic publications citing FactHarbor
278 278  * Referrals from fact-checking organizations
279 279  * Search engine results (ClaimReview schema visibility)
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283 283  === 5.2 Evaluation ===
284 284  
285 285  **What they assess**:
323 +
286 286  * Methodology documentation (open and detailed?)
287 287  * Sample analyses (quality and transparency?)
288 288  * Open-source code (auditable?)
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292 292  === 5.3 Adoption ===
293 293  
294 294  **How they start**:
333 +
295 295  * Submit a claim they're curious about
296 296  * Explore an existing analysis in depth
297 297  * Review methodology documentation
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301 301  === 5.4 Retention ===
302 302  
303 303  **Why they return**:
343 +
304 304  * Consistent quality and transparency
305 305  * Time savings in verification workflow
306 306  * Unique value (scenario analysis not available elsewhere)
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314 314  **Profile**: Users who want verdicts that confirm their existing beliefs
315 315  
316 316  **Why Not Ideal**:
357 +
317 317  * Will be frustrated by nuanced, scenario-based analysis
318 318  * May reject conclusions that don't match expectations
319 319  * Not looking for transparent reasoning—looking for validation
320 320  
321 321  **How to Handle**:
363 +
322 322  * Don't compromise methodology to satisfy them
323 323  * The transparency may eventually convert some
324 324  
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327 327  **Profile**: Users who only want instant answers, no interest in evidence
328 328  
329 329  **Why Not Ideal**:
372 +
330 330  * Don't value FactHarbor's core differentiator (transparency)
331 331  * Would be better served by simpler binary fact-checkers
332 332  * Won't engage with evidence or scenarios
333 333  
334 334  **How to Handle**:
378 +
335 335  * Provide quick summary views (UN-1: trust at a glance)
336 336  * Make deeper exploration available but not required
337 337  
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340 340  **Profile**: Users seeking to game or manipulate the system
341 341  
342 342  **Why Not Ideal**:
387 +
343 343  * Waste resources
344 344  * Damage system integrity
345 345  * Not genuine users
346 346  
347 347  **How to Handle**:
393 +
348 348  * AKEL detection of manipulation patterns
349 349  * Moderation for flagged escalations
350 350  * Transparent ban policies
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354 354  === 7.1 Segment Metrics ===
355 355  
356 356  Track for each segment:
403 +
357 357  * **Acquisition**: How many from each segment?
358 358  * **Activation**: Do they complete first analysis?
359 359  * **Engagement**: Do they explore evidence?
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362 362  
363 363  === 7.2 Segment-Specific Success Indicators ===
364 364  
365 -| Segment | Key Success Metric |
366 -|---------|-------------------|
367 -| Journalists | API calls per newsroom; time saved per verification |
368 -| Researchers | Papers citing FactHarbor; data downloads |
369 -| Educators | Curricula integrations; student engagement |
370 -| Policy Analysts | Briefings citing FactHarbor; repeat usage |
412 +| Segment | Key Success Metric |\\
413 +|-|-----|\\
414 +| Journalists | API calls per newsroom; time saved per verification |\\
415 +| Researchers | Papers citing FactHarbor; data downloads |\\
416 +| Educators | Curricula integrations; student engagement |\\
417 +| Policy Analysts | Briefings citing FactHarbor; repeat usage |\\
371 371  | Content Consumers | Retention rate; evidence exploration rate |
372 372  
373 373  === 7.3 Partnership Metrics ===
374 374  
375 -| Partner Type | Success Metric |
376 -|-------------|----------------|
377 -| Media | Integration count; co-published analyses |
378 -| Fact-Checkers | Data sharing volume; methodology alignment |
379 -| Academic | Papers published; grants received |
422 +| Partner Type | Success Metric |\\
423 +|-||\\
424 +| Media | Integration count; co-published analyses |\\
425 +| Fact-Checkers | Data sharing volume; methodology alignment |\\
426 +| Academic | Papers published; grants received |\\
380 380  | Funders | Grants awarded; renewal rate |
381 381  
382 382  == 8. Related Pages ==
383 383  
384 -* [[User Needs>>FactHarbor.Specification.Requirements.User Needs.WebHome]] - Detailed user need definitions
431 +* [[User Needs>>Archive.FactHarbor 2026\.02\.08.Specification.Requirements.User Needs.WebHome]] - Detailed user need definitions
385 385  * [[Requirements>>FactHarbor.Specification.Requirements.WebHome]] - How user needs map to requirements
386 386  * [[Partnership Strategy>>FactHarbor.Organisation.Partnership-Strategy]] - Partnership opportunity details
387 387  * [[Funding & Partnerships>>FactHarbor.Organisation.Funding-Partnerships]] - Funding sources and contacts
388 388  * [[Organisational Model>>FactHarbor.Organisation.Organisational-Model]] - How FactHarbor is structured
389 -