Eric Berlow and Sean Gourley: Mapping ideas worth spreading

70,684 views ・ 2013-09-18

TED


Ju lutemi, klikoni dy herë mbi titrat në anglisht më poshtë për të luajtur videon.

Translator: Alisa Xholi Reviewer: Helena Bedalli
00:12
Eric Berlow: I'm an ecologist, and Sean's a physicist,
0
12562
3061
Eric Berlow: Une jam nje ekolog dhe Sean eshte nje fizikant,
00:15
and we both study complex networks.
1
15623
2108
se bashku ne studiojme rrjete te nderlikuara.
00:17
And we met a couple years ago when we discovered
2
17731
1835
Jemi njohur disa vjet me pare kur zbuluam
00:19
that we had both given a short TED Talk
3
19566
2000
se na eshte dhene nga nje fjalim TED i shkurter
00:21
about the ecology of war,
4
21566
2303
mbi ekologjine e luftes,
00:23
and we realized that we were connected
5
23869
1447
dhe zbuluam se na bashkonin
00:25
by the ideas we shared before we ever met.
6
25316
2818
idete qe ndanim para se te njiheshim.
00:28
And then we thought, you know, there are thousands
7
28134
1556
Me pas menduam, se mund te kete me mijera
00:29
of other talks out there, especially TEDx Talks,
8
29690
2114
fjalime te tjera atje, mbi te gjitha fjalime te TEDx,
00:31
that are popping up all over the world.
9
31804
2211
qe po shfaqen ne te gjithe boten.
00:34
How are they connected,
10
34015
923
00:34
and what does that global conversation look like?
11
34938
2010
Si jane te lidhura ato ,
dhe si ngjason biseda globale?
00:36
So Sean's going to tell you a little bit about how we did that.
12
36948
2810
Sean do ju tregoje pak se si e beme ate.
00:39
Sean Gourley: Exactly. So we took 24,000 TEDx Talks
13
39758
3767
Sean Gourley: Pikerisht. Ne morem 24.000 fjalime TEDx
00:43
from around the world, 147 different countries,
14
43525
3046
nga e gjithe bota, 147 shtete te ndryshme,
00:46
and we took these talks and we wanted to find
15
46571
2123
ajo cka donim te gjenim ne keto fjalime ishte
00:48
the mathematical structures that underly
16
48694
2040
strukturat matematikore qe fshehin
00:50
the ideas behind them.
17
50734
1722
idete pas tyre.
00:52
And we wanted to do that so we could see how
18
52456
1370
Dhe donin ta benim kete ne menyre qe te shihnim
00:53
they connected with each other.
19
53826
2053
se si lidheshin ato mes tyre.
00:55
And so, of course, if you're going to do this kind of stuff,
20
55879
1676
Dhe sigurisht, nese do te besh dicka te tille,
00:57
you need a lot of data.
21
57555
956
te duhen shume te dhena.
00:58
So the data that you've got is a great thing called YouTube,
22
58511
3686
Dhe te dhenat qe ti ke eshte nje dicka e madhe qe quhet YouTube,
01:02
and we can go down and basically pull
23
62197
1768
ku mund te nxjerrim
01:03
all the open information from YouTube,
24
63965
2267
te gjithe informacionin e hapur nga YouTube,
01:06
all the comments, all the views, who's watching it,
25
66232
2349
te gjitha komentet, shikimet, kush po e sheh ate,
01:08
where are they watching it, what are they saying in the comments.
26
68581
2779
ku po e shohin dhe cfare po thone ne komente.
01:11
But we can also pull up, using speech-to-text translation,
27
71360
3292
Por mund edhe te nxjerrim, duke perdorur perkthimet nga te folurit ne tekste,
01:14
we can pull the entire transcript,
28
74652
2128
mund te perdorim te gjithe kopjen e shkruar,
01:16
and that works even for people with kind of funny accents like myself.
29
76780
2680
dhe kjo funksionon dhe per njerezit me dialekt pak qesharak si ky i imi.
01:19
So we can take their transcript
30
79460
2106
Pra ne mund te marim kopjen e shkruar
01:21
and actually do some pretty cool things.
31
81566
2098
dhe realisht te bejme disa gjera shume interesante.
01:23
We can take natural language processing algorithms
32
83664
2160
Mund te marim algoritme natyrore te perpunimit te gjuhes
01:25
to kind of read through with a computer, line by line,
33
85824
2629
per te lexuar me nje kompjuter, rrjesht pas rrjeshti,
01:28
extracting key concepts from this.
34
88453
2359
duke nxjerre koncepte kyce nga kjo.
01:30
And we take those key concepts and they sort of form
35
90812
2525
I marim keto koncepte kyce qe perbejne
01:33
this mathematical structure of an idea.
36
93337
3565
strukturen matematikore te nje ideje.
01:36
And we call that the meme-ome.
37
96902
1757
Dhe kete e quajme meme-ome.
01:38
And the meme-ome, you know, quite simply,
38
98659
2151
Meme-ome, shume thjesht
01:40
is the mathematics that underlies an idea,
39
100810
2426
eshte matematika ne bazen e nje ideje,
01:43
and we can do some pretty interesting analysis with it,
40
103236
1932
dhe mund te bejme nje analize shume interesante me te,
01:45
which I want to share with you now.
41
105168
1981
te cilen dua ta ndaj me ju.
01:47
So each idea has its own meme-ome,
42
107149
2190
Pra cdo ide ka meme-ome e vet,
01:49
and each idea is unique with that,
43
109339
1951
dhe cdo ide eshte unike,
01:51
but of course, ideas, they borrow from each other,
44
111290
2488
por sigurisht, idete, huazojne nga njera tjetra,
01:53
they kind of steal sometimes,
45
113778
1184
madje dhe vjedhin nga njera-tjetra ndonjehere,
01:54
and they certainly build on each other,
46
114962
1827
dhe sigurisht ndertohen mbi njera tjetren
01:56
and we can go through mathematically
47
116789
1616
keshtu mund te vazhdojme matematikisht
01:58
and take the meme-ome from one talk
48
118405
1840
dhe te marim meme-ome nga nje fjalim
02:00
and compare it to the meme-ome from every other talk,
49
120245
2454
dhe ta krahasojme ate me meme-ome me cdo fjalim tjeter,
02:02
and if there's a similarity between the two of them,
50
122699
1973
dhe nese ka ngjashmeri mes dy nga ato,
02:04
we can create a link and represent that as a graph,
51
124672
3250
mund te krijojme nje lidhje si grafik,
02:07
just like Eric and I are connected.
52
127922
2394
ashtu sic jam i lidhur une me Eric.
02:10
So that's theory, that's great.
53
130316
1394
Pra kjo eshte teori. Kjo eshte e mrekullueshme.
02:11
Let's see how it works in actual practice.
54
131710
2526
Le te shohim si funksionon ne praktike.
02:14
So what we've got here now is the global footprint
55
134236
2788
Ajo cka kemi ketu eshte gjurma globale
02:17
of all the TEDx Talks over the last four years
56
137024
2293
nga te gjitha fjalimet e TEDx per kater vitet e fundit
02:19
exploding out around the world
57
139317
1550
qe shperthejne ne bote
02:20
from New York all the way down to little old New Zealand in the corner.
58
140867
3329
nga New York deri ne Zelanden e Re ketu ne qoshe.
02:24
And what we did on this is we analyzed the top 25 percent of these,
59
144196
3835
Ajo cka beme ketu ishte analiza e 25 perqind te ketyre,
02:28
and we started to see where the connections occurred,
60
148031
2534
dhe filluam te shikonim se ku shfaqeshin lidhjet,
02:30
where they connected with each other.
61
150565
1537
atje ku bashkoheshin me njera tjetren.
02:32
Cameron Russell talking about image and beauty
62
152102
1874
Cameron Russell duke folur mbi imazhin dhe bukurine
02:33
connected over into Europe.
63
153976
1575
lidhet me te gjithe Europen.
02:35
We've got a bigger conversation about Israel and Palestine
64
155551
2412
Kemi nje diskutim me te madh mbi Israelin dhe Palestinen
02:37
radiating outwards from the Middle East.
65
157963
2255
e cila perhapet drejt Lindjes se Mesme.
02:40
And we've got something a little broader
66
160218
1298
Dhe kemi dicka me te gjere
02:41
like big data with a truly global footprint
67
161516
2156
si te dhena te medha me gjurme te verteta globale
02:43
reminiscent of a conversation
68
163672
2179
e cila ngjason me nje bisede
02:45
that is happening everywhere.
69
165851
2016
qe po ndodh kudo.
02:47
So from this, we kind of run up against the limits
70
167867
2173
Nga kjo, u gjendem disi kundrejt limiteve
02:50
of what we can actually do with a geographic projection,
71
170040
2530
nga cka mund te bejme realisht me projektimin gjeografik,
02:52
but luckily, computer technology allows us to go out
72
172570
2052
por fatmiresisht, teknologjia kompjuterike na lejon te dalim
02:54
into multidimensional space.
73
174622
1546
ne nje hapesire shume dimensionale.
02:56
So we can take in our network projection
74
176168
1875
Keshtu mund te marim projektin tone te rrjetit
02:58
and apply a physics engine to this,
75
178043
1750
dhe te aplikojme nje motor fizike ne kete,
02:59
and the similar talks kind of smash together,
76
179793
1885
keshtu fjalimet e ngjashme pak a shume perplasen me njera tjetren,
03:01
and the different ones fly apart,
77
181678
2004
kurse ato te ndryshmet vecohen,
03:03
and what we're left with is something quite beautiful.
78
183682
2072
dhe ajo cka na mbetet eshte dicka shume e bukur.
03:05
EB: So I want to just point out here that every node is a talk,
79
185754
2957
EB: Dua te nenvizoj ketu se cdo nyje eshte nje fjalim,
03:08
they're linked if they share similar ideas,
80
188711
2589
ato lidhen nese ndajne te njejtat ide,
03:11
and that comes from a machine reading
81
191300
2084
dhe kjo del nga nje mekanizem lexues
03:13
of entire talk transcripts,
82
193384
2067
i kopjes se shkruar ne teresi,
03:15
and then all these topics that pop out,
83
195451
2231
dhe me pas te gjitha subjektet qe ndahen,
03:17
they're not from tags and keywords.
84
197682
1790
nuk jane nga etiketimet ose fjalet kyce.
03:19
They come from the network structure
85
199472
1725
Ato vine nga struktura e rrjetit
03:21
of interconnected ideas. Keep going.
86
201197
2168
te ideve te nderlidhura. Vazhdo.
03:23
SG: Absolutely. So I got a little quick on that,
87
203365
2022
SG. Absolutisht. U nxitova pak aty,
03:25
but he's going to slow me down.
88
205387
1475
por ai do me ngadalsoje pak.
03:26
We've got education connected to storytelling
89
206862
2034
Kemi edukimin qe lidhet me tregimet
03:28
triangulated next to social media.
90
208896
1643
ne trekendesh me median sociale.
03:30
You've got, of course, the human brain right next to healthcare,
91
210539
2475
Keni sigurisht, trurin e njeriut prane kujdesit shendetesor,
03:33
which you might expect,
92
213014
1386
ku mund ta prisni,
03:34
but also you've got video games, which is sort of adjacent,
93
214400
2395
por gjithashtu keni dhe lojrat elektronike e cila eshte afer,
03:36
as those two spaces interface with each other.
94
216795
2740
ndersa keto dy hapesira interferojne me njera tjetren.
03:39
But I want to take you into one cluster
95
219535
1535
Por dua tju terheq ne nje grumbull
03:41
that's particularly important to me, and that's the environment.
96
221070
2868
qe eshte ne vecanti shume i rendesishem per mua, dhe ky eshte mjedisi.
03:43
And I want to kind of zoom in on that
97
223938
1493
Dhe dua ta zmadhoj pak ketu
03:45
and see if we can get a little more resolution.
98
225431
2363
dhe te shohim nese mund te marim nje rezolucion pak me te larte.
03:47
So as we go in here, what we start to see,
99
227794
2347
Pra duke u futur ketu, ajo cka fillojme te shohim,
03:50
apply the physics engine again,
100
230141
1504
duke aplikuar perseri motorin e fizikes,
03:51
we see what's one conversation
101
231645
1676
shohim se nje bisede
03:53
is actually composed of many smaller ones.
102
233321
2560
aktualisht eshte e perbere nga disa me te vogla.
03:55
The structure starts to emerge
103
235881
1929
Struktura fillon te shfaqet
03:57
where we see a kind of fractal behavior
104
237810
2070
ku shohim nje sjellje disi fraktale
03:59
of the words and the language that we use
105
239880
1619
e fjaleve dhe gjuhes qe perdorim
04:01
to describe the things that are important to us
106
241499
1702
per te pershkruar gjera qe jane interesante per ne
04:03
all around this world.
107
243201
1433
ne kete bote.
04:04
So you've got food economy and local food at the top,
108
244634
2332
Kemi ekonomine e ushqimit dhe ushqimin lokal ne skaj,
04:06
you've got greenhouse gases, solar and nuclear waste.
109
246966
2719
kemi gazrat e serrave, mbetjet diellore dhe berthamore.
04:09
What you're getting is a range of smaller conversations,
110
249685
2631
Ajo cka merrni eshte nje linje bisedash me te vogla,
04:12
each connected to each other through the ideas
111
252316
2301
te lidhura me njera tjetren ndermjet ideve
04:14
and the language they share,
112
254617
1301
dhe gjuhes qe ato ndajne,
04:15
creating a broader concept of the environment.
113
255918
2450
duke krijuar nje koncept me te gjere mbi mjedisin.
04:18
And of course, from here, we can go
114
258368
1532
Dhe sigurisht nga ketu, mund te shkojme
04:19
and zoom in and see, well, what are young people looking at?
115
259900
3534
dhe te zmadhojme e shohim, se cfare shohin te rinjte?
04:23
And they're looking at energy technology and nuclear fusion.
116
263434
2345
Ata shohin teknologjine energjitike dhe fusionin berthamor.
04:25
This is their kind of resonance
117
265779
1674
Kjo eshte rezonanca e tyre
04:27
for the conversation around the environment.
118
267453
2406
per bisedat mbi mjedisin.
04:29
If we split along gender lines,
119
269859
1899
Nese do ndajme linjat gjinore,
04:31
we can see females resonating heavily
120
271758
1987
mund te shohim se gjinia femerore anon me shume
04:33
with food economy, but also out there in hope and optimism.
121
273745
3645
ne ekonomine ushqimore, por gjithashtu ne shprese dhe optimizem.
04:37
And so there's a lot of exciting stuff we can do here,
122
277390
2482
Dhe keshtu kemi disa gjera shume interesante qe mund te bejme ketu,
04:39
and I'll throw to Eric for the next part.
123
279872
1762
dhe do tja kaloj Eric per pjesen tjeter.
04:41
EB: Yeah, I mean, just to point out here,
124
281634
1602
EB: Po, dua te them thjesht per te theksuar
04:43
you cannot get this kind of perspective
125
283236
1538
nuk mund ta maresh kete perspektive
04:44
from a simple tag search on YouTube.
126
284774
3360
nga nje etiketim i thjeshte ne YouTube.
04:48
Let's now zoom back out to the entire global conversation
127
288134
4188
Tani le te zmadhojme te gjitha bisedat globale
04:52
out of environment, and look at all the talks together.
128
292322
2534
nga mjedisi, dhe te shohim gjithe fjalimet bashke.
04:54
Now often, when we're faced with this amount of content,
129
294856
2927
Shpesh ne hasim kete sasi permbajtjeje,
04:57
we do a couple of things to simplify it.
130
297783
2431
dhe kryejme disa gjera per ti thjeshtuar.
05:00
We might just say, well,
131
300214
1314
Edhe mund te themi, ne rregull,
05:01
what are the most popular talks out there?
132
301528
2829
cilat jane fjalimet me te njohura aty?
05:04
And a few rise to the surface.
133
304357
1397
Dhe disa dalin ne siperfaqe.
05:05
There's a talk about gratitude.
134
305754
1828
Ekziston nje fjalim mbi mirenjohjen.
05:07
There's another one about personal health and nutrition.
135
307582
3344
Eshte dhe nje tjeter mbi shendetin personal dhe ushqimin.
05:10
And of course, there's got to be one about porn, right?
136
310926
2929
Dhe sigurisht duhet te kete dhe nje mbi pornografine apo jo?
05:13
And so then we might say, well, gratitude, that was last year.
137
313855
3234
Dhe atehere mund te themi, mirenjohja ishte vitin e kaluar.
05:17
What's trending now? What's the popular talk now?
138
317089
2522
Por cfare eshte ne qarkullim tani? Cili eshte fjalimi me i njohur tani?
05:19
And we can see that the new, emerging, top trending topic
139
319611
3321
Dhe mund te shohim se subjekti me ne qarkullim
05:22
is about digital privacy.
140
322932
2666
eshte ai mbi privatesine dixhitale.
05:25
So this is great. It simplifies things.
141
325598
1693
Pra kjo eshte e mrekullueshme. Kjo i thjeshton gjerat.
05:27
But there's so much creative content
142
327291
1827
Por ka kaq shume subjekte me krijuese
05:29
that's just buried at the bottom.
143
329118
1921
te cilat jane te varrosura ne fund.
05:31
And I hate that. How do we bubble stuff up to the surface
144
331039
3318
Dhe une e urrej kete. Si mund te nxjerrim ne siperfaqe gjera
05:34
that's maybe really creative and interesting?
145
334357
2458
te cilat mund te jene krijuese dhe interesante?
05:36
Well, we can go back to the network structure of ideas
146
336815
2931
Mund ti kthehemi struktures se rrjetit te ideve
05:39
to do that.
147
339746
1430
per ta bere.
05:41
Remember, it's that network structure
148
341176
2114
Mbani mend, eshte ajo strukture rrjeti
05:43
that is creating these emergent topics,
149
343290
2268
e cila krijon subjektet ne zhvillim,
05:45
and let's say we could take two of them,
150
345558
1515
dhe le te themi qe mund te marrim dy nga ato,
05:47
like cities and genetics, and say, well, are there any talks
151
347073
3047
si qytete dhe gjenetika dhe te themi, a ekzistojne fjalime
05:50
that creatively bridge these two really different disciplines.
152
350120
2569
qe krijimtarisht lidh keto dy disiplina vertet te ndryshme.
05:52
And that's -- Essentially, this kind of creative remix
153
352689
2275
Dhe kjo eshte --Ne thelb, ky lloj remiksi kreativ
05:54
is one of the hallmarks of innovation.
154
354964
1840
eshte nje nga shenjat dalluese te risis.
05:56
Well here's one by Jessica Green
155
356804
1606
Ketu kemi nje nga Jessica Green
05:58
about the microbial ecology of buildings.
156
358410
2379
mbi ekologjine mikrobiale te ndertesave.
06:00
It's literally defining a new field.
157
360789
2010
Kjo percakton vertet nje fushe te re.
06:02
And we could go back to those topics and say, well,
158
362799
2103
Dhe mund ti kthehemi ketyre subjekteve duke thene
06:04
what talks are central to those conversations?
159
364902
2768
cilat fjalime kryesojne ne keto biseda?
06:07
In the cities cluster, one of the most central
160
367670
1690
Ne grumbullin e qyteteve, nje nga me kryesoret
06:09
was one by Mitch Joachim about ecological cities,
161
369360
3952
eshte njera nga Mitch Joachim mbi ekologjine e qyteteve,
06:13
and in the genetics cluster,
162
373312
1720
dhe ne grumbullin e gjenetikes,
06:15
we have a talk about synthetic biology by Craig Venter.
163
375032
3193
kemi nje fjalim mbi biologjine sintetike nga Craig Venter.
06:18
These are talks that are linking many talks within their discipline.
164
378225
3353
Keto jane fjalime te cilat permbajne shume fjalime ne disiplinen e tyre.
06:21
We could go the other direction and say, well,
165
381578
1843
Mund te shkojme ne nje tjeter drejtim e te themi
06:23
what are talks that are broadly synthesizing
166
383421
2272
cilat jane fjalimet qe gjeresisht sintetizojne
06:25
a lot of different kinds of fields.
167
385693
1448
shume fusha te ndryshme.
06:27
We used a measure of ecological diversity to get this.
168
387141
2533
Ne perdorem nje mates mbi diversitetin ekologjik per ta marr kete.
06:29
Like, a talk by Steven Pinker on the history of violence,
169
389674
2736
Si fjalimi i Steven Pinker mbi historine e dhunes,
06:32
very synthetic.
170
392410
1180
shume sintetike.
06:33
And then, of course, there are talks that are so unique
171
393590
2078
Sigurisht keto jane fjalime shume te vecanta
06:35
they're kind of out in the stratosphere, in their own special place,
172
395668
3090
qe pak a shume jane jashte stratosferes ne vendin e tyre te vecante,
06:38
and we call that the Colleen Flanagan index.
173
398758
2514
dhe ne e quajme ate indeksi Colleen Flanagan.
06:41
And if you don't know Colleen, she's an artist,
174
401272
3034
Ne rast se nuk e njihni Collen, ajo eshte nje artiste,
06:44
and I asked her, "Well, what's it like out there
175
404306
1543
dhe une e pyeta ate, "Si eshte te jesh aty jashte
06:45
in the stratosphere of our idea space?"
176
405849
1672
ne stratosferen e hapesires se ideve?"
06:47
And apparently it smells like bacon.
177
407521
3255
Dhe me sa duket kishte nje ere si proshute e tymosur.
06:50
I wouldn't know.
178
410776
1791
Nuk kisha si ta dija.
06:52
So we're using these network motifs
179
412567
2248
Pra ne perdorim keto modele rrjeti
06:54
to find talks that are unique,
180
414815
1186
per te gjetur fjalime te vecanta,
06:56
ones that are creatively synthesizing a lot of different fields,
181
416001
2710
ato te cilat jane te sintetizuara krijimtarisht nga shume fusha te ndryshme,
06:58
ones that are central to their topic,
182
418711
1659
ato te cilat kryesojne subjektin e tyre,
07:00
and ones that are really creatively bridging disparate fields.
183
420370
3374
dhe ato te cilat lidhin krijimtarisht fusha te pangjashme.
07:03
Okay? We never would have found those with our obsession
184
423744
2102
Ne nuk mund ti gjenim ato kurre me manine
07:05
with what's trending now.
185
425846
2313
se cfare eshte ne qarkullim tani.
07:08
And all of this comes from the architecture of complexity,
186
428159
2886
Dhe e gjitha kjo vjen nga arkitektura e kompleksitetit,
07:11
or the patterns of how things are connected.
187
431045
2960
ose te modeleve te se si gjerat jane te lidhura.
07:14
SG: So that's exactly right.
188
434005
1625
SG: Kjo eshte ekzaktesisht e vertete.
07:15
We've got ourselves in a world
189
435630
2479
Jemi ne nje bote
07:18
that's massively complex,
190
438109
2044
e cila eshte masivisht komplekse,
07:20
and we've been using algorithms to kind of filter it down
191
440153
2867
dhe ne kemi perdorur algoritme per ta filtrurar ate
07:23
so we can navigate through it.
192
443020
1786
ne menyre qe ne te mund te lundrojme ne te.
07:24
And those algorithms, whilst being kind of useful,
193
444806
2338
Dhe keto algoritme ndersa jane shume te dobishme dhe te mira
07:27
are also very, very narrow, and we can do better than that,
194
447144
3476
jane gjithashtu dhe shume te kufizuara, dhe ne mund te bejme me shume se aq,
07:30
because we can realize that their complexity is not random.
195
450620
2566
sepse mund te kuptojme qe kompleksiteti i tyre nuk eshte i rastesishem.
07:33
It has mathematical structure,
196
453186
1954
Ka nje strukture matematikore,
07:35
and we can use that mathematical structure
197
455140
1803
dhe mund ta perdorim ate strukture matematikore
07:36
to go and explore things like the world of ideas
198
456943
2214
per te zbuluar gjera si boten e ideve
07:39
to see what's being said, to see what's not being said,
199
459157
3000
per te pare se cfare po thuhet, dhe cfare nuk po thuhet,
07:42
and to be a little bit more human
200
462157
1407
dhe per te qene pak me njerezor
07:43
and, hopefully, a little smarter.
201
463564
1867
dhe me shprese, pak me te zgjuar.
07:45
Thank you.
202
465431
966
Faleminderit.
07:46
(Applause)
203
466397
4220
(Duartrokitje)
Rreth kësaj faqe interneti

Kjo faqe do t'ju prezantojë me videot e YouTube që janë të dobishme për të mësuar anglisht. Do të shihni mësime angleze të mësuara nga mësues të nivelit më të lartë nga e gjithë bota. Klikoni dy herë mbi titrat në anglisht të shfaqura në secilën faqe të videos për të luajtur videon prej andej. Titrat lëvizin në sinkron me riprodhimin e videos. Nëse keni ndonjë koment ose kërkesë, ju lutemi na kontaktoni duke përdorur këtë formular kontakti.

https://forms.gle/WvT1wiN1qDtmnspy7