The analysis of Portuguese Universities Page like network is organised according to an overview of the page’s profile, institutional connections and the narrative thread afforded by the spatialization of the network; by looking at its whole and parts as well as the central and bridging nodes (Latour et al., 2012; Venturini et al., 2019; Omena & Amaral, 2019). The question of clusters’ formations is also addressed, moving to an in-depth analysis of page categories as a path to unveil the universities specific (institutional) interests.

Starting with a general overview, the scatterplot below (Figure 2) displays different Facebook metrics (variables) attached to a given university (nodes). Through the size of nodes, we see that Facebook typical forms of measurements can be very contradictory if taken as analytical parameters. For instance, a high degree of post activity may not relate with users’ engagement - talking about count (see the universities of UTAD, Coimbra and Algarve). In the same token, the number of fan count (see Aberta). In other words, a high degree of activity or number of fans not necessarily indicates high levels of engagement. Additionally, we see that more than a half of the universities allow users to post (green nodes), but these publications are kept hidden from their Page timeline.

Figure 3
n overview of Portuguese Universities according to the following Facebook metrics: post activity (posts per hour and based on the last 50 posts); talking about count (attention metric); users can post (whether a page allows users to publish posts on the page); fan count (number of likes a page has received). Scatterplot made in RawGraphs and edited in Inkscape.

When moving towards the heat map of the Portuguese Universities page like network (Figure 4), we first notice that Media and News Companies (see the nodes among Público and Expresso), followed by the Foundation Calouste Gulbenkian, at the heart of the interests of this network. A second aspect corresponds to a high density of connections that surrounds UTAD and Algarve universities and, with a lower density; ISCTE, Porto, NOVA e Lisboa. A third aspect concerns Madeira University which is detached from the main component within the network and, ironically, geographically isolated. Madeira is an island located in Funchal part of the Maderian archipelago. Following the positioning of the nodes, one final observation relates to the central role of Universia Portugal (an academic Portal), European Commission, Forum Estudante (an academic and professional-oriented magazine) and the Association of Portuguese Speaking Universities (AULP).

The exercise of replacing edges with a density heat map provides a vision of the whole network and signalise the matters of common concern among Portuguese Universities (Media and News Journal); pointing also to agglomerations (clusters) and central actors.

Figure 4
The heatmap of Portuguese Universities page like network corresponding to March 2019. The networks show 44 visible nodes (out of 1.522) and it contains 18.988 edges. Node size by indegree. Visualization by Graph Recipes (Heatmap dessert) and Gephi.

While recognising the value of the nodes positioned in the centre of the network (under the categories of Media/News Company and Newspapers), these nodes were removed with the intention to better visualise clusters. For instance (see Fig. 5), the emergence of three small clusters attached to the universities of Aveiro, Beira Interior and Minho. Furthermore, new central actors for Portuguese Universities were detected: the General Direction of Portuguese Higher Education, MIT Portugal Program (an international collaboration centre), FNAC Portugal and Futurália (the biggest Education Fair in Portugal). After that, we read the spatialisation of the network through the visual affordances of ForceAtlas2¹¹. In the centre of the network, we see the very connected pages that have a key role to the whole network, while influential actors and bridging nodes¹² take part in the mid-term field. For instance, the Portuguese television and radio channels (e.g. RTP2, SIC TV, Rádio Comercial), AULP and the job opportunities office as bridging nodes. In the mid-term, small clusters can be seeing with connections mainly related to Porto, Nova, Lisboa and Évora universities.

In the periphery (Fig. 5), while the large holes denote less connections with the centre or mid-term zones, the existence of clusters correspond to the particular interests of Algarve, UTAD, Minho, Beira Interior and ISCTE. For instance, faculties, laboratories, student associations, schools. As an isolated element, Madeira only takes part of the network due to the likes the page has received from a medical service and a high school Facebook Pages. Madeira university itself has only connected to pages featured by “Portugueses in...” or “Portuguese immigrants in...”, evoking to the presence of Portugueses in European, South America and African cities or countries. Those are, somehow, unexpected connections for an official higher-education Institutional Facebook Page.

Throughout the observation of the shape of edges in large and small clusters, a visual pattern is identified suggesting how clusters are formed. An outward movement from the central node to its neighbours alludes to the fact that cluster formation is substantially based on the act of liking (see Algarve, UTAD and ISCTE in Fig. 5). To confirm the visual hypothesis, we invoked degree centrality to analyse cluster formation within the page like network: by sizing nodes according to the number of connections made by a page (degree), and the total of likes a page received (indegree) or made (outdegree).

Figure 5
Reading the page like network of Portuguese Universities according to the narrative thread afforded by the force directed layout ForceAtlas2. The nodes categorised by Media/News Company and Newspapers were removed in order to highlight cluster formation and to see the universities particular interests. 1.426 nodes,16.125 edges. Node sized by degree.

We thus reimaged page likes (table 2) to define whether cluster formation is based on page activity (by means of liking pages), reciprocity (by a balanced number of likes made vs. received), popularity (by means of receiving likes), or little reciprocity. In so doing, we avoid misinterpretation in the process of interpreting digital networks, e.g. taking larger clusters as more important or overseeing the role of hidden elements.

Algarve has the largest cluster mainly because it has liked more than 500 pages. In contrast, the small cluster of Minho is based on reciprocal connections, while Porto seems to be very popular among other institutional Facebook Pages. When accounting for how connections are made within a network (data relational nature), node size or visibility should only inform different characteristics that serve as basis for understanding the cluster formation and its narrative thread.

Table 2
Analysing cluster formation and nodes size on the basis of in-degree and out-degree.

After understanding cluster formation, the Facebook parameter Page Category¹³ served as form of identifying the interests of Portuguese Universities (see Fig. 6) within the network. Not surprisingly, College & University, School, Community, Non-profit Organization, Community College, High School, Government Organization, and Media/News Company are the dominant categories within the network. Page category also reveals multiple dimensions of sociality: media and communication (TV, radio, newspaper, website); culture (museums, library, art, musician/band); business (company, consulting or advertising or marketing agency, agriculture service); public services and health concerns (medical and health, hospital); entertainment (golf course and country, cultural centre, movie theatre) and gastronomy (Thai restaurant, dessert shop); public figures and news personality. Even very specific interests like Barbershop, Car Dealership, Shopping Mall, Sports League and Events. However, when searching for political related categories, civic engagement, social movements or causes, nothing was found.

Figure 6
What are the dominant (highlighted in white) and ordinary (in colour) associations linked to Portuguese Universities? Treemap of Page Categories: size refers to the frequency of appearance.

Back to the mainstream categories, and driven by College & University and School, three groups that stand for the institutional profile and specific interests of each university were detected:

1. 1. Schools from varied districts/regions of Portugal; with especial attention to school groups (Algarve and UTAD), polytechnic institutes (Évora), university departments or services (Minho).
2. 2. Internal stakeholders; faculties, institutes, departments, research centres, and courses from each university. For instance, Coimbra, Lisboa and NOVA focus on their faculties or institutes, meanwhile Aveiro pays more attention to departments, Beira Interior to students’ nuclei from different courses, and Católica to courses including its branches in Porto and Braga.
3. 3. International universities and Portuguese higher education¹⁴ exclusively represented by ISCTE – IUL, and local learning centres.

Contrasting with this description, Aberta University is uniquely positioned in combination of the three groups due to its balanced range of connectivity. Another affordance of looking at page categories is unfolding official pages that are set aside by the university or the other way around. A good example is the lack of connection between Coimbra University and its Department of Physics, The geophysical and astronomic laboratory, The geophysical and astronomic laboratory, Rádio Universidade de Coimbra, and others¹⁵. Additionally, the discovery of pages oriented towards specific audience, e.g. Brazilians students¹⁶.

What can we foresee from a historical dataset of Facebook images timelines? How to repurpose the methods of the medium to study the visuality of higher education in Portugal? As natively digital objects, online images have uniform resource identifiers (URLs) that often provides a fragment component preceded by a = (equal sign) which points to an unique identifier (id) of a given image, such as https://scontent.flis9-1.fna.fbcdn.net/v/t1.0-9/1937274_144956263379_7335679_n.jpg?_nc_cat=108&_nc_ht=scontent.flis9-1.fna&oh=2a719e0099e71e-4049305a22ea628887&oe=5D536D7D. By taking advantage of the image’s URLs afforded by Facebook Graph API and merging these into the computer vision services of Google Cloud API, we were able to describe and interpret the imagery of Portuguese Universities.

A total of 22.594 images were plotted in a bipartite network, in which nodes are images (90.62%) and labels (9.38%), while edges (161.474 in total) show the connections made by a number of labels that describe one or more images. The co-occurrences of similar descriptive visual content (labels) informs the position of the images within the network. In alignment with Rose’s (2016) proposal for interpret visual material, the first level of analysis enquires about the site of the image itself. The multi-sited composition and meanings indicate different formations of institutional interests that are invested in the visuality of the page timelines. What visualities describe this culture? What the dominant visualities and their inherent meanings can tell? What is not there (and why)? Through the computer vision API-based network, in Figure 7, we see the plot of all images featured in the timeline of the 15 Portuguese Universities Facebook Pages, and spatialised according to correlated labels. At the bottom, the analytical exercise of relabelling the machine vision by categorising clusters. In what follows we will present how the scrutiny of timeline images can provided general and specific insights on the visual culture of Portuguese Universities over the years, more precisely from each university page created time to March 2018.

In Figure 7, at the top, we see a quite homogeneous network; except from the strong concentration of images in dark hues on the right side and the colourful agglomeration at the top. These clusters represent the most common visual representation associated with Portuguese Universities official Facebook Pages: Portugal sentado (Portugal while seated) and posters. The former is named after a Portuguese journalistic expression that relates to the (bad) habit of publishing photos of people seated in press conferences, auditoriums, all kinds of meetings, parliament, scientific conferences, or even sports events. In order words, something to be avoided in the newspapers. Posters depict all sort of written content: screenshots of news, institutional newsletter, banners to promote academic events or to celebrate commemorative dates.

In the peripheral zone of the image-label network, the formation of discrete clusters that points to different visualities with a more detailed classification (labels) to describe the images, whereas a more generic labelling takes place in the centre of the network. After analysing the different regions of the network, ten clusters were detected beyond those two already mentioned (see Fig. 7): people in academic events, people in outdoor/indoor events, school buildings, head shot pictures, sports, musical performance, sky and grass, animals, labs, and history in blackandwhite.

Figure 7
The imagery of Portuguese Universities on Facebook from 2009 to 2018.

In a general view (Fig. 8), the visual depiction of Portuguese Universities mainly outlines the tedious pictures of audiences (sitting in an auditorium) or keynote speakers in academic conferences. Adding to that, pre and post conference conversations, organizers or participants posing to pictures, posters presentations, institutional partnership (e.g. hands shaking or signing contracts) and prize winners. Next to portugal sentado and nearly the center of the network (Fig. 7), there are two other clusters which main focus is people in academic events (outdoor and indoor activities); also, small and big groups chatting or posing for photo, professors or students being interviewed.

Another strong visual identity is the graphical depiction of posters and banners with the most varied type of announcements. Beyond conference, symposiums, workshops, sports or new students related banners, number of likes achieved by a page (fan count), and the celebration around the ‘international day of’ (e.g. water, statistics). A very particular visuality is also uncovered; that is news clipping which indicates how Portuguese Universities value when mainstream or traditional Portuguese newspapers headlines or mentions academic research, professors or students. In this scenario, and between 2009 and 2018, we may infer that the dominant visualities of Portuguese Universities conform to people attending events and institutional posters.

The architecture of school buildings earned a place of honour, in particular the overwhelming presence of Institute of Social Sciences (ICS) of Minho University (Fig. 8). We also visualise head shot pictures of local, national and international researchers (perhaps a few number of students), and a full cluster dedicated to university sports (Fig.8). From collective (including wheelchair categories) to individuals’ modalities, the rule seems to be the depiction of victorious teams; images of teams celebrating the victory, athletes on the podium, holding medals or a trophy. At the bottom of the network, the musical performance cluster (Fig. 7), composed by cultural events in the shape of concerts, choirs, orchestra and musicians with their instruments. There is also a group of images putting together because sky and grass are their main visual composition.

Figure 8
The visual history of Portuguese Universities from 2009 to 2018: image tree map based on clusters detected in the image-label network (portugal sentado, posters, people in academic events, people in outdoor/indoor events, school buildings, head shot pictures, sports, musical performance, sky and grass, animals, labs, and history in black and white).

The ordinary visual content (less substantial in numbers) brings wild and domestic animals such as birds, caws, awls, tigers, monkey, dogs and cats; the stereotype images of labs - namely researchers working with a telescope; and people who made history in black and white pictures. This latter, therefore, basically represents historical photos published by Porto. The visual description and historical perspective of Portuguese Universities seem to lack, however, the everyday life of students and non-stereotypical imagery of scientific research, while it overvalued the academic events and institutional communication through banners and news clippin

Figure 9
Vision API-based network grid. Seeing the visual patterns of a given Portuguese University from its page created time to March 2018.

After having a general (but also detailed) perspective on the imagery of Portuguese Universities on Facebook, in the second level of analysis, we questioned about the visual choices and patterns attached to each university. Fifteen bipartite image-label networks were arranged in a grid to respond to this question (Fig. 9). The focus of our analytical observations here is on the presence or absence of colours, which indicates different visual patterns and particularities. In the grid, for each university image-label network there is the number of images in accordance with the page created time. These individual characteristics helps in to situate different networks. The vision API-based network grid provides not only an innovative technique to approach Portuguese Universities’ timeline images but their visual history on Facebook.

As previously described, pictures of sitting audiences, posters and people in academic conferences, correspond to the dominant imagery of the majority of Portuguese universities on Facebook – with exception of Coimbra University. In contrast to this portrayal, the practice of sports and musical performance appear to have little visual space among universities, at least if compared with the main images’ categories. For instance, there is a minor representation in Açores, Lisboa and Católica and no visual mention in Madeira. Aberta University does not contemplate sport practices. Particular characteristics can be seen through the animals cluster which is almost exclusively to UTAD but also represented in Porto and, on a minor scale, in Aveiro. The head shot pictures seems to please all universities, except in the case of Açores, Madeira, Coimbra; these latter do not invest in such style. The vision API-based network grid (Fig. 9) offers an effective and direct way of reading the choices and patterns that constitute the imagery of Portuguese University on Facebook. Such technique can be replicated for other similar studies.

Since people is at the core of the visual communication, the last level of analysis took advantage of the face detection module made available by Google Vision API. The main objective was to repurpose machine vision to assess the mood of Portuguese higher education. Results demonstrate an overwhelming depiction of happiness along the years, but also detect other face expressions such as surprise, sorrow and anger (see Fig. 10). In terms of consistency, and considering the page created time, Porto, Minho, Aveiro, ISCTE and Madeira have recursively publishing images that contain joy in their respective Facebook Pages. Whereas, in terms of volume and duration, Trás-os-Montes e Alto Douro (775 images), Açores (603 images), Évora (447 images) and Beira Interior (285 images) stand out as the Facebook Pages with more images that are very likely or likely to express joy. But what are those images related to? What would be the motive for great happiness or pleasure? After plotting images separately (see appendices), it was possible to uncover the different motives that drives the visual imagery of UTAD, Açores, Évora and Beira Interior.

The happiness in UTAD is mainly featured by students, staff or professors posing for a picture in varied types of academic events, and the depiction of smiling speakers and audience. There is also joy in head shot pictures, news clipping, people drinking wine, in a few selfies, sports, tech related pics, and the inauguration of new facilities. In a similar spirit, the visuality of Beira Interior has a great focus on students participating in outdoor and indoor events. Although it also brings university staff and board members in these events, some selfies, head shot pictures and the register of awards ceremonies. The smiling audience, the act of posing for pictures in academic events and official ceremonies are also key visual characteristics in Évora, added by the overwhelming presence of students. Other types of events prompt the happy visuality of Açores: official ceremonies to award the best graduated students (both in an auditorium and in the rectory building); events where the faculty staff and board members get together, e.g. in the rectory building, outdoor picnic. Photos of students in classroom, in the rectory building or in outdoor events are also common.

Beyond the academic events that put together students, professors, staff and board members, there is a common reason that brings joy to the higher-educational environment; the visit of the president of Portugal, Marcelo Rebelo de Sousa. His presence is synonymous of a series of pictures in the Facebook timeline images of UTAD, Açores, Évora and Beira Interior universities. The International Exchange Erasmus Students Network connects also to the joy of Évora and Beira Interior, and although sporting achievement are too little, these images often connect to felicity.

When further analysing the other face expressions, the results supplied by computer vision can be deceptive. The Facebook timeline images that contain surprise (64 images) do not exactly depict faces showing that something unexpected may have happened. Rather, we see face expressions that may be tricky for machine learning algorithms, e.g. to raise eyebrows or open and close the mouth when talking or giving a presentation. Although useless for detecting real surprised faces, the results provided by machine vision demonstrate a type of visuality that should perhaps be avoided in institutional communication; for not offering a pleasant visual identity (e.g. a, b, c, d, e).

Figure 10
Computer vision for seeing the mood of Portuguese Universities over the years according to face detection module of Google Vision API. Four main expression were detected as very likely or likely to appear in the universities Facebook images timeline: joy, surprise, sorrow and anger.

The sorrow related images (a total of 14) are mainly groups of students in different situations such as: in learning environments when they appear to be very concentrated and sitting in a small auditorium or standing in a laboratory paying attention to the professor (e.g. in Açores and in UTAD); in academic events (e.g. 1 and 2 from UTAD, and e.g. 3 from Aveiro); or students being interviewed by a television reporter (Algarve). Institutional and academic events also categorise a few sorrow images, e.g. university staff happen to appear in organising or planning activities in an educational event (Beira Interior), a picture zooming in focused audience sitting in an auditorium (Açores), and when a university receives the president of Portugal, Marcelo Rebelo de Sousa who, accompanied by the dean of Évora University (Ana Costa Freitas) and board members, was walking up stairs to enter the university building (Évora). There is also the case of detecting sorrow faces in banners; one promoting an exhibition about the miracles of Nossa Senhora de Fátima constituted by an old black and white photo with three children staring at a camera and looking all sad (UTAD), another with Alfred Hitchcock looking down another filmmaker (Évora).

The five images with anger faces derive from the practice of sports, except for the promotion of the Masters in Theatre of Évora University in 2017. The other cases bring winner athletes such as João Paulo Fernandes who get the second place in London Paralympic Games 2012 (Aveiro); the celebration of Porto’s female Rugby team for third place in the European University Games 2014 (Porto); the image of Minho´s female five-a-side football athletes in the middle of the court celebrating (probably the victory) in 2017 (Minho), or the applications for EA Campus 2014 (ISCTE).

The thick description about face detection, in particular surprise, sorrow and anger, intentionally calls our attention to the lack of precision and limitations of computer vision APIs.